Triple
T22630254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southeast Asia (through Agent Orange deployment) |
E558528
|
entity |
| Predicate | timePeriodOfExposure |
P302
|
FINISHED |
| Object | 1960s |
—
|
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: 1960s | Statement: [Southeast Asia (through Agent Orange deployment), timePeriodOfExposure, 1960s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timePeriodOfExposure Context triple: [Southeast Asia (through Agent Orange deployment), timePeriodOfExposure, 1960s]
-
A.
exposureTime
Indicates the duration for which a subject or object is exposed to a particular condition, influence, or medium.
-
B.
exposureType
Indicates the specific manner or context in which one entity is exposed to another entity, condition, or influence.
-
C.
timePeriod
chosen
Indicates the specific span or interval of time during which an event, state, or relationship occurs or is valid.
-
D.
exposureLevel
Indicates the degree or intensity to which an entity is subjected or exposed to a particular factor, condition, or influence.
-
E.
timeOfShooting
Indicates the specific time at which a shooting event occurs.
- 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_69e245467d9881908d6985bd0db7a1f1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17008e7648190b243c18067b4efb9 |
completed | April 29, 2026, 2:42 a.m. |
| PD | Predicate disambiguation | batch_69ee62855558819080da946c7b35a160 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 17, 2026, 3:02 p.m.