Triple
T1477269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dadra and Nagar Haveli and Daman and Diu |
E30869
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Diu
Diu is a coastal town and former Portuguese colonial enclave on India’s western coast, known for its historic fort, churches, and beaches.
|
E169638
|
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: Diu | Statement: [Dadra and Nagar Haveli and Daman and Diu, hasCity, Diu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Diu Context triple: [Dadra and Nagar Haveli and Daman and Diu, hasCity, Diu]
-
A.
Gonda
Gonda is a city in the Indian state of Uttar Pradesh, known for its agricultural economy and proximity to the Ghaghara River.
-
B.
Mella
Mella is a Spanish-language surname most notably associated with Cuban revolutionary leader Julio Antonio Mella.
-
C.
Dainzú
Dainzú is an ancient Zapotec archaeological site in Oaxaca, Mexico, notable for its terraced architecture and carved stone reliefs depicting ballgame scenes.
-
D.
Micali
Micali is an Italian surname most notably associated with Silvio Micali, a Turing Award–winning computer scientist and cryptographer.
-
E.
Celeirós
Celeirós is a civil parish in the municipality of Sabrosa in northern Portugal, known for its traditional Douro wine production and historic rural landscape.
- 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: Diu Triple: [Dadra and Nagar Haveli and Daman and Diu, hasCity, Diu]
Generated description
Diu is a coastal town and former Portuguese colonial enclave on India’s western coast, known for its historic fort, churches, and beaches.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Diu Target entity description: Diu is a coastal town and former Portuguese colonial enclave on India’s western coast, known for its historic fort, churches, and beaches.
-
A.
Gonda
Gonda is a city in the Indian state of Uttar Pradesh, known for its agricultural economy and proximity to the Ghaghara River.
-
B.
Mella
Mella is a Spanish-language surname most notably associated with Cuban revolutionary leader Julio Antonio Mella.
-
C.
Dainzú
Dainzú is an ancient Zapotec archaeological site in Oaxaca, Mexico, notable for its terraced architecture and carved stone reliefs depicting ballgame scenes.
-
D.
Micali
Micali is an Italian surname most notably associated with Silvio Micali, a Turing Award–winning computer scientist and cryptographer.
-
E.
Celeirós
Celeirós is a civil parish in the municipality of Sabrosa in northern Portugal, known for its traditional Douro wine production and historic rural landscape.
- 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_69a498fe55a88190ab7f9e40ace88e49 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c603f9e88190b340734709534860 |
completed | March 1, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad15add78c8190843efd75bbe8423f |
completed | March 8, 2026, 6:22 a.m. |
| NEDg | Description generation | batch_69ad184626f48190a15ee8bb4f9f6f7c |
completed | March 8, 2026, 6:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad18dca6b48190a63b67a7823611c8 |
completed | March 8, 2026, 6:36 a.m. |
Created at: March 1, 2026, 8:11 p.m.