Triple
T2517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harry S. Truman |
E47
|
entity |
| Predicate | militaryRank |
P342
|
FINISHED |
| Object | Captain |
—
|
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: Captain | Statement: [Harry S. Truman, militaryRank, Captain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: militaryRank Context triple: [Harry S. Truman, militaryRank, Captain]
-
A.
honorificRank
Indicates that one entity holds a formal title or honorific status in relation to another entity.
-
B.
hasMilitaryBranch
Indicates that an entity is associated with, served in, or is part of a specific branch of a military organization.
-
C.
hasAcademicRank
Indicates that an entity holds a specific academic rank or title within an educational or research institution.
-
D.
positionHeld
Indicates that an entity occupies or has occupied a specific role, job, office, or position within an organization or context.
-
E.
militaryConflict
Indicates a relationship where two or more parties are engaged in organized, armed hostilities or warfare against each other.
- 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_69a22e0d37588190897cf37a323013f5 |
completed | Feb. 27, 2026, 11:51 p.m. |
| NER | Named-entity recognition | batch_69a2346846608190b6b40d31f1dbd685 |
completed | Feb. 28, 2026, 12:18 a.m. |
| PD | Predicate disambiguation | batch_69a233c396ec8190986608d07fb251d4 |
completed | Feb. 28, 2026, 12:16 a.m. |
| PDg | Predicate description generation | batch_69a2346794cc8190afce97b703903389 |
completed | Feb. 28, 2026, 12:18 a.m. |
Created at: Feb. 27, 2026, 11:55 p.m.