Triple
T7271232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santa Cruz Islands |
E161106
|
entity |
| Predicate | administrativeCenter |
P1474
|
FINISHED |
| Object | Lata |
E113454
|
NE FINISHED |
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: Lata | Statement: [Santa Cruz Islands, administrativeCenter, Lata]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lata Context triple: [Santa Cruz Islands, administrativeCenter, Lata]
-
A.
Lata
chosen
Lata is the main town and administrative center of Temotu Province in the eastern Solomon Islands.
-
B.
Lata
Lata is the given name of Lata Mangeshkar, the legendary Indian playback singer renowned as the "Nightingale of India."
-
C.
Lasya
Lasya is a graceful, expressive classical Indian dance style traditionally associated with feminine beauty and gentle, fluid movements.
-
D.
Latika
Latika is a central character in the film "Slumdog Millionaire," portrayed as the protagonist's childhood friend and love interest whose life intertwines with his journey from the Mumbai slums to game-show fame.
-
E.
Lavani
Lavani is a vibrant and rhythmic folk dance and musical style from Maharashtra, known for its powerful dholki beats, expressive storytelling, and often sensuous performances.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c6885181008190b419040e22939c7c |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb0a03888190b5aa1da80dd303c5 |
completed | March 27, 2026, 8:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7eed8c5448190b83faee62f8122de |
completed | March 28, 2026, 3:08 p.m. |
Created at: March 27, 2026, 2:58 p.m.