Triple
T5865556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Autódromo Hermanos Rodríguez |
E130382
|
entity |
| Predicate | hasSeatingArea |
P2608
|
FINISHED |
| Object | Foro Sol grandstands |
—
|
LITERAL 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: Foro Sol grandstands | Statement: [Autódromo Hermanos Rodríguez, hasSeatingArea, Foro Sol grandstands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeatingArea Context triple: [Autódromo Hermanos Rodríguez, hasSeatingArea, Foro Sol grandstands]
-
A.
hasSeating
chosen
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
B.
hasSeat
Indicates that one entity possesses, provides, or includes a seat for another entity.
-
C.
hasPassengerArea
Indicates that an object or vehicle includes a designated area intended for carrying passengers.
-
D.
hasShelteredSeating
Indicates that an entity provides seating that is protected from weather or other external elements.
-
E.
seatingCapacity
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
- F. None of above.
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_69c0085047dc8190af24e311edad3c07 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ffaef081909faaa7f420a3b9b7 |
completed | March 22, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69c03347e51c81909053bcf34e3b88ab |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:56 p.m.