Triple
T4456022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gertrudis |
E97724
|
entity |
| Predicate | hasSibling |
P363
|
FINISHED |
| Object | Tita De la Garza |
E388925
|
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: Tita De la Garza | Statement: [Gertrudis, hasSibling, Tita De la Garza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tita De la Garza Context triple: [Gertrudis, hasSibling, Tita De la Garza]
-
A.
Tita De la Garza
chosen
Tita De la Garza is the passionate, magically gifted protagonist of Laura Esquivel’s novel "Like Water for Chocolate," whose emotions infuse the food she cooks.
-
B.
Gertrudis De la Garza
Gertrudis De la Garza is a passionate and rebellious character from Laura Esquivel’s novel "Like Water for Chocolate," known for defying her strict family and societal expectations.
-
C.
Carmen Cortez
Carmen Cortez is a resourceful young spy and one of the two sibling protagonists in the Spy Kids film series.
-
D.
María Elena
María Elena is a small Chilean mining town in the Antofagasta Region, historically known as one of the last nitrate (saltpeter) company towns in the world.
-
E.
María Elena
María Elena is a passionate, volatile Spanish artist portrayed by Penélope Cruz in the film "Vicky Cristina Barcelona."
- 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_69b3454777808190b78aa9047ba1f018 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3564216b081908c41109100b36862 |
completed | March 13, 2026, 12:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b63767f8d08190a58cc441471adf90 |
completed | March 15, 2026, 4:36 a.m. |
Created at: March 12, 2026, 11:33 p.m.