Triple
T38591145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Imperial Agent |
E932455
|
entity |
| Predicate | canSpecializeAs |
P166149
|
FINISHED |
| Object | Operative |
—
|
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: Operative | Statement: [Imperial Agent, canSpecializeAs, Operative]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canSpecializeAs Context triple: [Imperial Agent, canSpecializeAs, Operative]
-
A.
specializesTo
chosen
Indicates that one entity is a more specific or specialized version of another, inheriting its characteristics while adding further constraints or detail.
-
B.
isSpecializedFor
Indicates that one entity is specifically adapted, designed, or focused to perform optimally for a particular function, context, or domain associated with another entity.
-
C.
usableBySpecialization
Indicates that something can be used specifically by entities with a particular specialization or role.
-
D.
allowsSpecializationIn
Indicates that one entity grants permission or provides the option for another entity to pursue a specific specialization within it.
-
E.
exportSpecialization
Indicates a relationship where one entity specializes in exporting particular goods, services, or resources to another entity or market.
- 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_69f76ec654d48190b421111cf26e54d9 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcf36d2894819089b7db8e91b63c9d |
completed | May 7, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69fcf25c0a108190bfa823474098640b |
completed | May 7, 2026, 8:13 p.m. |
Created at: May 3, 2026, 4:32 p.m.