Triple
T3780016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jama Masjid, Ahmedabad |
E85393
|
entity |
| Predicate | nearby |
P350
|
FINISHED |
| Object |
Teen Darwaza
Teen Darwaza is a historic triple-arched gateway in Ahmedabad, India, renowned as one of the city’s oldest and most iconic architectural landmarks.
|
E387753
|
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: Teen Darwaza | Statement: [Jama Masjid, Ahmedabad, nearby, Teen Darwaza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Teen Darwaza Context triple: [Jama Masjid, Ahmedabad, nearby, Teen Darwaza]
-
A.
Badal
Badal is a Barcelona Metro station that serves the area near Camp Nou stadium in Barcelona, Spain.
-
B.
Ghari
Ghari is an Oceanic language spoken in the Solomon Islands, belonging to the Meso-Melanesian branch of the Austronesian language family.
-
C.
Spin Ghar
Spin Ghar is a prominent mountain range in eastern Afghanistan forming part of the border with Pakistan and known for its rugged, high peaks.
-
D.
Andaz
Andaz is a luxury boutique hotel brand known for its contemporary design, locally inspired experiences, and personalized service.
-
E.
Aayega Aanewala
"Aayega Aanewala" is a landmark Hindi film song from the 1949 movie Mahal, celebrated for its haunting melody and for bringing playback singer Lata Mangeshkar to national prominence.
- 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: Teen Darwaza Triple: [Jama Masjid, Ahmedabad, nearby, Teen Darwaza]
Generated description
Teen Darwaza is a historic triple-arched gateway in Ahmedabad, India, renowned as one of the city’s oldest and most iconic architectural landmarks.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Teen Darwaza Target entity description: Teen Darwaza is a historic triple-arched gateway in Ahmedabad, India, renowned as one of the city’s oldest and most iconic architectural landmarks.
-
A.
Badal
Badal is a Barcelona Metro station that serves the area near Camp Nou stadium in Barcelona, Spain.
-
B.
Ghari
Ghari is an Oceanic language spoken in the Solomon Islands, belonging to the Meso-Melanesian branch of the Austronesian language family.
-
C.
Spin Ghar
Spin Ghar is a prominent mountain range in eastern Afghanistan forming part of the border with Pakistan and known for its rugged, high peaks.
-
D.
Andaz
Andaz is a luxury boutique hotel brand known for its contemporary design, locally inspired experiences, and personalized service.
-
E.
Aayega Aanewala
"Aayega Aanewala" is a landmark Hindi film song from the 1949 movie Mahal, celebrated for its haunting melody and for bringing playback singer Lata Mangeshkar to national prominence.
- 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_69aed937fa8881908208ef3801060826 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee3d84d7881909828903896b3cb7f |
completed | March 9, 2026, 3:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4f040676c8190aa3a7952a9d6f62b |
completed | March 14, 2026, 5:21 a.m. |
| NEDg | Description generation | batch_69b4f159d7e88190a76d51378ba141d3 |
completed | March 14, 2026, 5:25 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4f220f9388190b2c3615f713f01f2 |
completed | March 14, 2026, 5:29 a.m. |
Created at: March 9, 2026, 3:12 p.m.