Triple
T34507296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apollo 13 |
E885921
|
entity |
| Predicate | causalFactorOfAccident |
P694
|
FINISHED |
| Object | damaged oxygen tank and thermostat switch issue |
—
|
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: damaged oxygen tank and thermostat switch issue | Statement: [Apollo 13, causalFactorOfAccident, damaged oxygen tank and thermostat switch issue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causalFactorOfAccident Context triple: [Apollo 13, causalFactorOfAccident, damaged oxygen tank and thermostat switch issue]
-
A.
causedAccident
Indicates that one entity is responsible for bringing about or initiating an accident involving another entity or situation.
-
B.
depictedCauseOfAccident
Indicates that one entity is shown or represented as the cause of an accident involving another entity.
-
C.
causeOf
chosen
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
-
D.
causeOfInjury
Indicates that one entity is the source or reason that another entity sustained an injury.
-
E.
resultOfAccident
Indicates that something exists or occurs as a consequence or outcome of an accident.
- 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_69f349cc0220819081f154c6964f4dc2 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71fb1ab3881908e2f7c0e6f23db49 |
completed | May 3, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f71cc6397881909aaad37a9daa8a7e |
completed | May 3, 2026, 10 a.m. |
Created at: May 1, 2026, 2:01 a.m.