Triple
T33178072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsurumai Station |
E849238
|
entity |
| Predicate | hasJROperatorAbbreviation |
P176403
|
FINISHED |
| Object | JR Central |
—
|
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: JR Central | Statement: [Tsurumai Station, hasJROperatorAbbreviation, JR Central]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasJROperatorAbbreviation Context triple: [Tsurumai Station, hasJROperatorAbbreviation, JR Central]
-
A.
otherOperatorAbbreviation
Indicates that one operator is referred to or represented by an alternative abbreviated form used by another operator.
-
B.
hasNameAbbreviation
Indicates that an entity is associated with a shortened or abbreviated form of its full name.
-
C.
canBeUsedWithAbbreviation
Indicates that one entity (such as a term, phrase, or expression) is suitable to be used together with a particular abbreviation.
-
D.
usesAbbreviationOf
Indicates that one entity employs a shortened or abbreviated form of the name or designation of another entity.
-
E.
hasAbbreviationStatus
Indicates that an entity has a particular status or condition regarding its abbreviation (e.g., whether it is abbreviated, how, or to what extent).
- 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_69f3495d06508190b0b7729982982cea |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6e02ba6b881908dfafc52d3b75f1c |
completed | May 3, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69f6de09c2f481909f8b2545d3208c9f |
completed | May 3, 2026, 5:32 a.m. |
| PDg | Predicate description generation | batch_69f6e029f0f88190b1f88d82a4a2cabd |
completed | May 3, 2026, 5:42 a.m. |
Created at: May 1, 2026, 1:29 a.m.