Triple
T3722752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilson |
E81676
|
entity |
| Predicate | hasStationHouse |
P47116
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Wilson, hasStationHouse, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStationHouse Context triple: [Wilson, hasStationHouse, yes]
-
A.
hasStationBuilding
Indicates that a station is associated with or includes a station building as part of its facilities.
-
B.
hasStationStructure
chosen
Indicates that an entity possesses or is associated with a particular station-related physical structure.
-
C.
hasNotableStation
Indicates that an entity possesses or is associated with a station that is considered notable or significant in some context.
-
D.
hasStageHouse
Indicates that a performance venue or theater includes or is equipped with a stage house as part of its structure.
-
E.
hasPublicHouse
Indicates that one entity possesses, operates, or is associated with a public house (such as a bar or pub) as part of its facilities or holdings.
- 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_69ad8b1b7ef081908d2d381bbf54985a |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adca9ea1688190b3b8414d77960e8f |
completed | March 8, 2026, 7:14 p.m. |
| PD | Predicate disambiguation | batch_69adc0436e508190909ec4a3e8443aef |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:34 p.m.