Triple
T14872873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smara |
E349793
|
entity |
| Predicate | hasRoadConnectionTo |
P11435
|
FINISHED |
| Object |
Tan-Tan
Tan-Tan is a town in southwestern Morocco known as a gateway to the Sahara and for its annual cultural festival celebrating Sahrawi and nomadic heritage.
|
E1124282
|
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: Tan-Tan | Statement: [Smara, hasRoadConnectionTo, Tan-Tan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tan-Tan Context triple: [Smara, hasRoadConnectionTo, Tan-Tan]
-
A.
Tin Tan
Tin Tan was a hugely popular Mexican actor, comedian, and singer, best known for his pachuco persona and influential roles in the Golden Age of Mexican cinema.
-
B.
Tomomi
Tomomi is a Japanese given name that can be used for people of any gender.
-
C.
Takkaze
Takkaze is a river in northern Ethiopia that flows through deep gorges before joining the Atbarah River, ultimately contributing to the Nile basin.
-
D.
Toshi
Toshi is a Japanese given name commonly used for both males and females, often as a short form of longer names such as Toshiro or Toshiko.
-
E.
Rine-chan
Rine-chan is a female cheerleader-style mascot character for the Japanese professional baseball team Chiba Lotte Marines.
- 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: Tan-Tan Triple: [Smara, hasRoadConnectionTo, Tan-Tan]
Generated description
Tan-Tan is a town in southwestern Morocco known as a gateway to the Sahara and for its annual cultural festival celebrating Sahrawi and nomadic heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tan-Tan Target entity description: Tan-Tan is a town in southwestern Morocco known as a gateway to the Sahara and for its annual cultural festival celebrating Sahrawi and nomadic heritage.
-
A.
Tin Tan
Tin Tan was a hugely popular Mexican actor, comedian, and singer, best known for his pachuco persona and influential roles in the Golden Age of Mexican cinema.
-
B.
Tomomi
Tomomi is a Japanese given name that can be used for people of any gender.
-
C.
Takkaze
Takkaze is a river in northern Ethiopia that flows through deep gorges before joining the Atbarah River, ultimately contributing to the Nile basin.
-
D.
Toshi
Toshi is a Japanese given name commonly used for both males and females, often as a short form of longer names such as Toshiro or Toshiko.
-
E.
Rine-chan
Rine-chan is a female cheerleader-style mascot character for the Japanese professional baseball team Chiba Lotte Marines.
- 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_69d822ee4f408190b6ac3b2fa434f0df |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded5e2c94c8190a16f05ea81701fc1 |
completed | April 15, 2026, 12:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe65129a588190bbad294b500f411f |
completed | May 8, 2026, 10:34 p.m. |
| NEDg | Description generation | batch_69fe66a5f3a88190827c6c9247323153 |
completed | May 8, 2026, 10:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe6736ff34819098524e4401a414aa |
completed | May 8, 2026, 10:44 p.m. |
Created at: April 10, 2026, 1:55 a.m.