Triple
T9138203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1985 Mexico City earthquake |
E219257
|
entity |
| Predicate | buildingsCollapsed |
P1583
|
FINISHED |
| Object | thousands of buildings |
—
|
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: thousands of buildings | Statement: [1985 Mexico City earthquake, buildingsCollapsed, thousands of buildings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: buildingsCollapsed Context triple: [1985 Mexico City earthquake, buildingsCollapsed, thousands of buildings]
-
A.
buildingsDestroyed
chosen
Indicates that one or more buildings have been damaged to the point of destruction as a result of some event or action.
-
B.
towerCollapsedIn
Indicates that a tower underwent structural failure and collapsed at or within a specified location or context.
-
C.
roofCollapsed
Indicates that the roof of a structure has given way or fallen in, typically due to structural failure or external forces.
-
D.
originalBuildingDestroyedBy
Indicates that the original building was destroyed as a result of the actions or effects of the specified agent or cause.
-
E.
previousBuildingDemolished
Indicates that a building which previously occupied the same site or fulfilled the same role has been demolished.
- 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_69ca83e012288190a5771058adbaabd2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8efe3b88190a55a15827e6817a4 |
completed | April 1, 2026, 5:11 a.m. |
| PD | Predicate disambiguation | batch_69cc6601d77881908299d58db6e64937 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:19 p.m.