Triple
T6803888
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gasoline Alley garages |
E156251
|
entity |
| Predicate | primaryUseDuring |
P10000
|
FINISHED |
| Object | Indianapolis 500 race month |
—
|
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: Indianapolis 500 race month | Statement: [Gasoline Alley garages, primaryUseDuring, Indianapolis 500 race month]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryUseDuring Context triple: [Gasoline Alley garages, primaryUseDuring, Indianapolis 500 race month]
-
A.
usedPrimarilyIn
chosen
Indicates that something is mainly or most commonly employed within a particular context, domain, or purpose.
-
B.
primaryUseInFeed
Indicates that something is the main or most common way an item is used or presented within a feed.
-
C.
laterPrimarilyUsedFor
Indicates that something was initially used for one purpose but, at a later time, came to be used mainly for another specified purpose.
-
D.
usedDuring
Indicates that one entity is employed, applied, or active in the course of another entity’s process, event, or time period.
-
E.
primaryMode
Indicates the main or most commonly used method, manner, or form in which an action, process, or interaction is carried out between entities.
- 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_69c68826e6a48190a3d220b541e639de |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2e8d7888190a837620967a150e3 |
completed | March 27, 2026, 6:56 p.m. |
| PD | Predicate disambiguation | batch_69c6d099bf08819089a9f9894d037e74 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:16 p.m.