Triple
T27173328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Exxon Valdez |
E682975
|
entity |
| Predicate | flagAtTimeOfAccident |
P161934
|
FINISHED |
| Object | United States |
—
|
NE NERFINISHED |
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: United States | Statement: [Exxon Valdez, flagAtTimeOfAccident, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: flagAtTimeOfAccident Context triple: [Exxon Valdez, flagAtTimeOfAccident, United States]
-
A.
accidentOccurredDuring
Indicates that an accident took place within the time span or context of a specified event, activity, or condition.
-
B.
hasAccidentAt
Indicates that an accident involving a subject occurs at a specific location or time.
-
C.
accidentPhase
Indicates the specific stage or phase of progression within an accident or incident event.
-
D.
injuryOccurredAt
Indicates that an injury took place at a specific location or during a particular event or time.
-
E.
fuelLocationAtTimeOfAccident
Indicates the specific location of fuel at the moment when the accident occurred.
- 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_69eefad086808190ab89816c0c300476 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f62549039c8190af7159d07416c985 |
completed | May 2, 2026, 4:24 p.m. |
| PD | Predicate disambiguation | batch_69f61b40f02081909bd9c3ea73249163 |
completed | May 2, 2026, 3:41 p.m. |
| PDg | Predicate description generation | batch_69f61fa35ac48190890102c348ed81a0 |
completed | May 2, 2026, 4 p.m. |
Created at: April 27, 2026, 9:24 a.m.