Triple
T37872795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Tillers |
E944645
|
entity |
| Predicate | enemyTypeOpposed |
P189791
|
FINISHED |
| Object | virmen |
—
|
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: virmen | Statement: [The Tillers, enemyTypeOpposed, virmen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: enemyTypeOpposed Context triple: [The Tillers, enemyTypeOpposed, virmen]
-
A.
enemyType
Indicates that one entity is classified as an enemy of a specified type or category in relation to another entity.
-
B.
enemyElement
Indicates that one entity is an opposing or adversarial counterpart to another within a given context or system.
-
C.
enemyForceType
Indicates that one entity is characterized as a hostile or opposing force of a specified type relative to another entity.
-
D.
opposingUnits
Indicates that two units are in opposition to each other, such as being on rival sides, conflicting forces, or competing entities within a given context.
-
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_69f76eef55d481908ca6660b4b532550 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbca6c066c8190a1599202f341417f |
completed | May 6, 2026, 11:10 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ee04f08190977b7ad70fc85896 |
completed | May 6, 2026, 11:04 p.m. |
| PDg | Predicate description generation | batch_69fbc993caa881908c16c3e21efaeef9 |
completed | May 6, 2026, 11:07 p.m. |
Created at: May 3, 2026, 4:19 p.m.