Triple
T11732772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elisabeth of Swabia |
E278939
|
entity |
| Predicate | placeOfDeath |
P21
|
FINISHED |
| Object | Toro |
E266545
|
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: Toro | Statement: [Elisabeth of Swabia, placeOfDeath, Toro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toro Context triple: [Elisabeth of Swabia, placeOfDeath, Toro]
-
A.
Toro
Toro is the bull mascot representing California State University, Dominguez Hills at its athletic events and campus activities.
-
B.
Toro
chosen
Toro is a historic town in the province of Zamora, Castile and León, Spain, known for its medieval architecture and wine production.
-
C.
Toro
Toro is a Marvel Comics supervillain and member of the Invaders, often depicted as a powerful, bull-like adversary.
-
D.
Toro
Toro is the traditional nickname of Torino F.C., a historic Italian football club based in Turin.
-
E.
Toro
Toro is the official bull-themed mascot of the NFL's Houston Texans, known for entertaining fans at games and team events.
- 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_69d6aaffec6881908bead509e8621742 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4daa7f48190896fc7653e9dd70b |
completed | April 10, 2026, 7:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef8406fe8881909722ecb040087e68 |
completed | April 27, 2026, 3:43 p.m. |
Created at: April 8, 2026, 9:41 p.m.