Triple
T30974106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Smith's Stadium |
E789180
|
entity |
| Predicate | hasSeatingSection |
P31103
|
FINISHED |
| Object | Kilimanjaro Stand |
—
|
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: Kilimanjaro Stand | Statement: [John Smith's Stadium, hasSeatingSection, Kilimanjaro Stand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeatingSection Context triple: [John Smith's Stadium, hasSeatingSection, Kilimanjaro Stand]
-
A.
hasSeatingSections
chosen
Indicates that an entity is divided into distinct seating areas or sections designated for occupants.
-
B.
stadiumSectionOf
Indicates that one entity is a specific section or subdivision within a larger stadium.
-
C.
hasSeatingClassification
Indicates that an entity is assigned a specific type or category of seating arrangement or capacity.
-
D.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
E.
hasSeatAt
Indicates that an entity occupies or holds a place, position, or membership within a specific group, body, or location.
- 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_69f224c4831c8190be53924ec25a150a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fed09a12648190affcd9bacf7ca275 |
completed | May 9, 2026, 6:13 a.m. |
| PD | Predicate disambiguation | batch_69fecf91d6f481908deb60c965c433ed |
completed | May 9, 2026, 6:09 a.m. |
Created at: April 29, 2026, 8:55 p.m.