Triple
T5702857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One Eyed Bastard |
E125708
|
entity |
| Predicate | groupCharacterization |
P65675
|
FINISHED |
| Object | brutal |
—
|
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: brutal | Statement: [One Eyed Bastard, groupCharacterization, brutal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: groupCharacterization Context triple: [One Eyed Bastard, groupCharacterization, brutal]
-
A.
membershipCharacteristic
Indicates that an entity possesses a specific attribute or quality by virtue of its membership in a particular group or category.
-
B.
scopeCharacterization
Indicates how the extent, boundaries, or coverage of something is defined, described, or qualified in relation to another entity or context.
-
C.
findingCharacterization
Indicates that a finding is being described or classified in terms of its nature, features, or diagnostic significance.
-
D.
demographicsCharacteristic
Indicates that one entity serves as a demographic attribute or characteristic (such as age, gender, ethnicity, etc.) that describes or classifies another entity.
-
E.
ruleCharacterization
Indicates that one rule is described, defined, or characterized in terms of another rule or set of rules.
- 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_69c0082c96988190b3a6a201edce472a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02456efb48190bf3aaabcc77cda92 |
completed | March 22, 2026, 5:18 p.m. |
| PD | Predicate disambiguation | batch_69c021c2d8bc8190b947c7d1f423d2f3 |
completed | March 22, 2026, 5:07 p.m. |
| PDg | Predicate description generation | batch_69c023dfec6881909ee6189b874b4348 |
completed | March 22, 2026, 5:16 p.m. |
Created at: March 22, 2026, 3:45 p.m.