Triple
T30368834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Los Angeles Metro fare system |
E772496
|
entity |
| Predicate | fareMediumBrand |
P61256
|
FINISHED |
| Object | TAP |
—
|
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: TAP | Statement: [Los Angeles Metro fare system, fareMediumBrand, TAP]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fareMediumBrand Context triple: [Los Angeles Metro fare system, fareMediumBrand, TAP]
-
A.
fareBrand
chosen
Indicates the specific fare category or brand under which a ticket or booking is sold, defining its associated rules, benefits, and restrictions.
-
B.
favoriteBrand
Indicates that one entity is the preferred or most liked brand of another entity.
-
C.
catalogBrand
Indicates that a brand is associated with, or offered within, a particular catalog.
-
D.
usedBrandOf
Indicates that one entity made use of or operated an item, product, or service associated with a particular brand.
-
E.
pickupBrand
Indicates that a pickup vehicle is associated with or produced by a particular brand.
- 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_69f2248d71408190aec0d5c2001b1cff |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f682825f408190b6510f20015c4e52 |
completed | May 2, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69f678d019fc8190913662cd2f87b857 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 29, 2026, 7:59 p.m.