Triple
T4542412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fratton Park |
E107564
|
entity |
| Predicate | hasAllSeaterStands |
P57595
|
FINISHED |
| Object | partly |
—
|
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: partly | Statement: [Fratton Park, hasAllSeaterStands, partly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAllSeaterStands Context triple: [Fratton Park, hasAllSeaterStands, partly]
-
A.
isAllSeater
Indicates that the entity provides only seated accommodation, with no standing room available.
-
B.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
C.
hasSeatingPose
Indicates that an entity is in a seated posture or arrangement, specifying how it is positioned while sitting.
-
D.
hasSeat
Indicates that one entity possesses, provides, or includes a seat for another entity.
-
E.
hasStandsType
Indicates that an entity has or is associated with a particular type or category of stands (e.g., display stands, support stands, or similar structures).
- 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_69bd43f922788190b7edfa294e39b178 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57d3be988190bf118c4a87415613 |
completed | March 20, 2026, 2:21 p.m. |
| PD | Predicate disambiguation | batch_69bd5220e40481908ca2d7e2c43d8531 |
completed | March 20, 2026, 1:56 p.m. |
| PDg | Predicate description generation | batch_69bd56f6e75481909c487a94a2c2d0ba |
completed | March 20, 2026, 2:17 p.m. |
Created at: March 20, 2026, 1:04 p.m.