Triple
T11377620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mahalaxmi |
E269509
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Tardeo |
E919146
|
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: Tardeo | Statement: [Mahalaxmi, adjacentTo, Tardeo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tardeo Context triple: [Mahalaxmi, adjacentTo, Tardeo]
-
A.
Tardeo
chosen
Tardeo is an upscale commercial and residential neighborhood in South Mumbai, India, known for its high-rise buildings, offices, and proximity to key city landmarks.
-
B.
Tarde
Tarde is a horse racing track associated with the legendary American Thoroughbred racehorse Native Dancer.
-
C.
La Riposa
La Riposa is a mountain refuge and common base for hikers ascending Rocciamelone in the Italian Alps.
-
D.
Hastière
Hastière is a municipality in the Walloon region of southern Belgium, known for its scenic Meuse River setting and historic religious architecture.
-
E.
Madruga
Madruga is a municipality in western Cuba known for its rural character and location within the historical region surrounding Havana.
- 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_69d6aacca1048190b39dbbc2174616fa |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7fc30f5d48190bb273df4c9e583a9 |
completed | April 9, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e55697b2388190929d7e0b15d809ba |
completed | April 19, 2026, 10:26 p.m. |
Created at: April 8, 2026, 9:33 p.m.