Triple
T13715746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | C09 |
E328892
|
entity |
| Predicate | signageUse |
P32040
|
FINISHED |
| Object | station identification |
—
|
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: station identification | Statement: [C09, signageUse, station identification]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: signageUse Context triple: [C09, signageUse, station identification]
-
A.
hasSignage
Indicates that appropriate signs or visual markers are present to convey information, directions, warnings, or identification related to the associated entity.
-
B.
hasSignageIn
Indicates that appropriate signs or signage for an entity are present or installed within a specified location or area.
-
C.
signageStandard
Indicates that something conforms to, follows, or specifies a particular standard or convention for signage.
-
D.
hasSignageType
chosen
Indicates the specific category or kind of signage associated with an object, location, or entity.
-
E.
scriptUsedInSignage
Indicates that a particular writing system or script is employed in the text or graphics of a sign or signage.
- 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_69d80770b9bc81909f70c8c317d53cff |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dd43973cf08190a417d0cca9dd314a |
completed | April 13, 2026, 7:27 p.m. |
| PD | Predicate disambiguation | batch_69dbbe92d77c81908e0244cffb7f78c5 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:54 p.m.