Triple
T1168140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1992 Summer Olympics |
E24846
|
entity |
| Predicate | torchLighterOccupation |
P25475
|
FINISHED |
| Object | Paralympic archer |
—
|
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: Paralympic archer | Statement: [1992 Summer Olympics, torchLighterOccupation, Paralympic archer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: torchLighterOccupation Context triple: [1992 Summer Olympics, torchLighterOccupation, Paralympic archer]
-
A.
torchLighter
Indicates that one entity lights, ignites, or operates a torch for another entity or in relation to another entity.
-
B.
hasLighting
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
C.
lightLevel
Indicates the intensity or amount of light present in a given context or environment.
-
D.
lightRange
Indicates the distance or area over which a light source effectively emits or illuminates.
-
E.
hasRelativeOccupation
Indicates that two people are related in such a way that one’s occupation is defined or characterized in relation to the other’s occupation.
- 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_69a494082a7c819095004f423f294a64 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bccef84481908864e819884af86c |
completed | March 1, 2026, 10:25 p.m. |
| PD | Predicate disambiguation | batch_69a4bb548c1481909092626c572d8782 |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bc8ae87c81908ca5d94f63ad0e80 |
completed | March 1, 2026, 10:24 p.m. |
Created at: March 1, 2026, 7:45 p.m.