Triple
T5865843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pat Tillman |
E130389
|
entity |
| Predicate | reasonForEnlistment |
P67572
|
FINISHED |
| Object | response to the September 11 attacks |
—
|
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: response to the September 11 attacks | Statement: [Pat Tillman, reasonForEnlistment, response to the September 11 attacks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForEnlistment Context triple: [Pat Tillman, reasonForEnlistment, response to the September 11 attacks]
-
A.
ageAtEnlistment
Indicates the age a person was when they enlisted in a service, organization, or role.
-
B.
enlistedIn
Indicates that an individual has formally joined and is serving in a particular military or service organization.
-
C.
volunteerOrConscript
Indicates that an entity participates in a role, service, or activity either by choosing to do so voluntarily or by being compelled or drafted into it.
-
D.
hadMilitaryObligationsTo
Indicates that one party was bound by duty or law to provide military service, support, or protection to another party.
-
E.
musteredIntoService
Indicates that an entity has been formally enrolled or assembled into active duty or official service under an authority.
- 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_69c0085047dc8190af24e311edad3c07 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ffaef081909faaa7f420a3b9b7 |
completed | March 22, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69c03347e51c81909053bcf34e3b88ab |
completed | March 22, 2026, 6:22 p.m. |
| PDg | Predicate description generation | batch_69c044fe17d08190b9bf47b13863ef52 |
completed | March 22, 2026, 7:37 p.m. |
Created at: March 22, 2026, 3:56 p.m.