Triple
T38225814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Italian Livorno Division |
E1012140
|
entity |
| Predicate | hasCombatantType |
P204552
|
FINISHED |
| Object | regular army unit |
—
|
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: regular army unit | Statement: [Italian Livorno Division, hasCombatantType, regular army unit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCombatantType Context triple: [Italian Livorno Division, hasCombatantType, regular army unit]
-
A.
hasCombatType
Indicates that an entity is associated with a particular mode or category of combat it uses or participates in.
-
B.
hasCombatantRole
Indicates that an entity participates in a conflict or battle in a specific combat-related role or capacity.
-
C.
hasCombatantSide
Indicates a relationship where a conflict, battle, or war is associated with one of the participating sides or factions involved in the combat.
-
D.
hasCombat
Indicates that an entity engages in, is involved with, or possesses the capability for combat or fighting interactions with other entities.
-
E.
hasOpposingForceType
Indicates that one force is characterized as being of a type that opposes or counteracts another force.
- 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_69f76dd25e0c81909f2abd0803e5e3ee |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a1c850c819088795a7ae59bdeb8 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037c84ecbc81908232e5215355f43b |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:30 p.m.