Triple
T4959698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Janpath |
E111373
|
entity |
| Predicate | hasSection |
P35
|
FINISHED |
| Object |
Tibetan Market
Tibetan Market is a popular open-air bazaar in New Delhi known for its Tibetan handicrafts, jewelry, clothing, and souvenirs.
|
E482483
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Tibetan Market | Statement: [Janpath, hasSection, Tibetan Market]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tibetan Market Context triple: [Janpath, hasSection, Tibetan Market]
-
A.
Osh Bazaar
Osh Bazaar is a large, bustling open-air market in Bishkek, Kyrgyzstan, known for its wide array of local foods, textiles, and traditional goods.
-
B.
Wunti Market
Wunti Market is a major traditional commercial hub in Bauchi, Nigeria, known for its bustling trade in foodstuffs, textiles, and everyday goods.
-
C.
Dantokpa Market
Dantokpa Market is a vast open-air marketplace in Cotonou, Benin, known as one of West Africa’s largest and busiest commercial hubs.
-
D.
Kinari Bazaar
Kinari Bazaar is a famous traditional market in Old Delhi known for its ornate wedding accessories, decorative trimmings, and festive fabrics.
-
E.
Mandilas Market
Mandilas Market is a bustling commercial hub on Lagos Island in Nigeria, known for its dense concentration of shops and traders dealing in clothing, textiles, and assorted goods.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Tibetan Market Triple: [Janpath, hasSection, Tibetan Market]
Generated description
Tibetan Market is a popular open-air bazaar in New Delhi known for its Tibetan handicrafts, jewelry, clothing, and souvenirs.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tibetan Market Target entity description: Tibetan Market is a popular open-air bazaar in New Delhi known for its Tibetan handicrafts, jewelry, clothing, and souvenirs.
-
A.
Osh Bazaar
Osh Bazaar is a large, bustling open-air market in Bishkek, Kyrgyzstan, known for its wide array of local foods, textiles, and traditional goods.
-
B.
Wunti Market
Wunti Market is a major traditional commercial hub in Bauchi, Nigeria, known for its bustling trade in foodstuffs, textiles, and everyday goods.
-
C.
Dantokpa Market
Dantokpa Market is a vast open-air marketplace in Cotonou, Benin, known as one of West Africa’s largest and busiest commercial hubs.
-
D.
Kinari Bazaar
Kinari Bazaar is a famous traditional market in Old Delhi known for its ornate wedding accessories, decorative trimmings, and festive fabrics.
-
E.
Mandilas Market
Mandilas Market is a bustling commercial hub on Lagos Island in Nigeria, known for its dense concentration of shops and traders dealing in clothing, textiles, and assorted goods.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69bd4418390c8190b7e9766a2512ce55 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd71da80008190a0d606d5091822b8 |
completed | March 20, 2026, 4:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be81e4ccc4819090223633fdb04eee |
completed | March 21, 2026, 11:32 a.m. |
| NEDg | Description generation | batch_69be83c923e08190848def2824a268b8 |
completed | March 21, 2026, 11:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be84d36c74819097a88f29ef409d20 |
completed | March 21, 2026, 11:45 a.m. |
Created at: March 20, 2026, 1:32 p.m.