Triple
T4432946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Notre Dame Stadium |
E95376
|
entity |
| Predicate | addedPermanentLights |
P1280
|
FINISHED |
| Object | 2011 |
—
|
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: 2011 | Statement: [Notre Dame Stadium, addedPermanentLights, 2011]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: addedPermanentLights Context triple: [Notre Dame Stadium, addedPermanentLights, 2011]
-
A.
hasLighting
chosen
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
B.
numberOfLights
Indicates the quantity of lights associated with or present on a given entity.
-
C.
lightSourceGeneration
Indicates that an entity produces or emits light, serving as a source of illumination for other entities or the environment.
-
D.
lightSourceFor
Indicates that one entity serves as the source of illumination for another entity.
-
E.
hasNightRaceLighting
Indicates that the subject facility or venue is equipped with lighting suitable for hosting events or activities at night.
- 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_69b3453c2a0c8190926b574c90766db9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3556cd83881908547aa311c4f17fa |
completed | March 13, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69b34f6078cc8190831b89f404198cc5 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:31 p.m.