Triple
T12787222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boomer |
E305662
|
entity |
| Predicate | positionRelativeToPrimaryMascot |
P95425
|
FINISHED |
| Object | secondary |
—
|
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: secondary | Statement: [Boomer, positionRelativeToPrimaryMascot, secondary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionRelativeToPrimaryMascot Context triple: [Boomer, positionRelativeToPrimaryMascot, secondary]
-
A.
relativePositionInStadium
chosen
Indicates the spatial relationship between entities based on where they are located relative to each other within a stadium.
-
B.
positionOfEmblem
Indicates the spatial placement or location of an emblem relative to a reference object or surface.
-
C.
positionInPark
Indicates that one entity occupies a specific location or spot within a park.
-
D.
hasMouthPositionRelativeToCity
Indicates the spatial position of a river’s mouth in relation to a specified city.
-
E.
positionOnIdentity
Indicates a stance, view, or opinion that an entity holds regarding identity-related issues or characteristics.
- 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_69d7bdf366888190a8cccb982606889c |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e5dbdb88190a1b06721ada51627 |
completed | April 10, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69d9640ba0688190973e4e7ec8d4a8e0 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:29 p.m.