Triple
T23516523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rail Bhavan, New Delhi |
E574382
|
entity |
| Predicate | locatedInCapitalCityOf |
P5025
|
FINISHED |
| Object | India |
—
|
NE NERFINISHED |
How this triple was built (2 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: India | Statement: [Rail Bhavan, New Delhi, locatedInCapitalCityOf, India]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: India Context triple: [Rail Bhavan, New Delhi, locatedInCapitalCityOf, India]
-
A.
India
chosen
India is a large South Asian country known for its vast population, cultural and linguistic diversity, and rapid economic growth.
-
B.
India
"India" is a popular song by American rapper Lil Durk, known for its melodic style and romantic themes.
-
C.
India
"India" is a 1969 Argentine erotic drama film directed by Armando Bó and starring Isabel Sarli, known for its sensual themes and iconic status in Latin American cult cinema.
-
D.
Inde
The Inde is a small river in western Germany and eastern Belgium that flows through North Rhine-Westphalia before joining the Rur.
-
E.
La India
La India is a Puerto Rican-American salsa singer renowned for her powerful voice and influential contributions to Latin music.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245bb3dcc8190ba9a2b35972b58d0 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1aa82a8448190bf7ad56137c5eb94 |
completed | April 29, 2026, 6:51 a.m. |
Created at: April 17, 2026, 6:08 p.m.