Triple
T15809237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2010 San Bruno pipeline explosion |
E383301
|
entity |
| Predicate | homesDamaged |
P992
|
FINISHED |
| Object | more than three dozen homes damaged or destroyed |
—
|
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: more than three dozen homes damaged or destroyed | Statement: [2010 San Bruno pipeline explosion, homesDamaged, more than three dozen homes damaged or destroyed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: homesDamaged Context triple: [2010 San Bruno pipeline explosion, homesDamaged, more than three dozen homes damaged or destroyed]
-
A.
damagedIn
chosen
Indicates that an entity has suffered harm, impairment, or destruction as a result of a specified event, process, or condition.
-
B.
houseBurned
Indicates that a house has been destroyed or significantly damaged by fire.
-
C.
infrastructureDamage
Indicates damage or destruction affecting physical infrastructure such as buildings, roads, utilities, or other constructed facilities.
-
D.
houses
Indicates that one entity serves as a dwelling or shelter for another entity.
-
E.
house2
Indicates a relationship where one entity is a secondary, related, or alternative house associated with another entity.
- 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_69d86da2858c819090cc8481e7207b6e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b529c6b481909664153ecc381f7c |
completed | April 16, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69e0053b847c8190945726c3ddac21cc |
completed | April 15, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:48 a.m.