Triple
T22642400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teatro de Santa Isabel |
E558863
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Saint Isabel |
—
|
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: Saint Isabel | Statement: [Teatro de Santa Isabel, namedAfter, Saint Isabel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saint Isabel Context triple: [Teatro de Santa Isabel, namedAfter, Saint Isabel]
-
A.
Saint Isabel
chosen
Saint Isabel is a Christian saint traditionally associated with charity, humility, and service to the poor, venerated in various regions that bear her name.
-
B.
Santa Isabel
Santa Isabel is a supermarket chain in Latin America operated under the retail group Cencosud.
-
C.
Santa Isabel
Santa Isabel is a municipality in the state of São Paulo, Brazil, known for its preserved natural areas and role as part of the greater São Paulo region.
-
D.
Santa Isabel
Santa Isabel is a Santiago Metro station on Line 5 located in the central area of Chile’s capital city.
-
E.
Santa Isabel
Santa Isabel is an urban neighborhood within the Carabayllo district of Lima, Peru.
- 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_69e24547f7fc819086e2c4ba3b979657 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1703489a48190bd97a7eb7a571b64 |
completed | April 29, 2026, 2:43 a.m. |
Created at: April 17, 2026, 3:04 p.m.