Triple
T445783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nassau Hall |
E7015
|
entity |
| Predicate | significantBuildingFire |
P13308
|
FINISHED |
| Object | 1802 fire |
—
|
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: 1802 fire | Statement: [Nassau Hall, significantBuildingFire, 1802 fire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: significantBuildingFire Context triple: [Nassau Hall, significantBuildingFire, 1802 fire]
-
A.
significantBuilding
Indicates that a building holds notable importance, prominence, or special status within a particular context (e.g., historical, cultural, architectural, or functional).
-
B.
significantInfrastructure
Indicates that an entity constitutes an important or critical piece of infrastructure within a system, network, or region.
-
C.
fireRescue
Indicates a relationship where one entity performs or is responsible for rescuing people or property from fires or fire-related emergencies involving another entity.
-
D.
significantMonument
Indicates that something is a monument of notable historical, cultural, or symbolic importance.
-
E.
buildingsDestroyed
Indicates that one or more buildings have been damaged to the point of destruction as a result of some event or action.
- 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_69a2e7e4676c81909ea0dbdecac0687c |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ef479ec08190a659eead6eb0d4d0 |
completed | Feb. 28, 2026, 1:36 p.m. |
| PD | Predicate disambiguation | batch_69a2eddfb5508190a4e06e1b260d8b2b |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eeb9e6b0819093863959a6e5730a |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.