Triple
T138865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hollywood/Vine station |
E2807
|
entity |
| Predicate | hasSignage |
P5950
|
FINISHED |
| Object | bilingual English–Spanish signage |
—
|
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: bilingual English–Spanish signage | Statement: [Hollywood/Vine station, hasSignage, bilingual English–Spanish signage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSignage Context triple: [Hollywood/Vine station, hasSignage, bilingual English–Spanish signage]
-
A.
signageStandard
Indicates that something conforms to, follows, or specifies a particular standard or convention for signage.
-
B.
hasLogoText
Indicates that an entity’s logo includes specific textual content or wording.
-
C.
hasCurrencySignPlacement
Indicates where the currency sign is positioned relative to the numeric amount in a monetary value.
-
D.
hasTypeOfInsignia
Indicates that an entity bears or is associated with a specific kind or category of insignia.
-
E.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
- F. None of above. chosen
Provenance (4 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257a800148190be119d1d075869b8 |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a2565426c08190aab68e34a6a2d60e |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a25737f9188190b9690dce98aed83a |
completed | Feb. 28, 2026, 2:47 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.