Triple
T33310148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles Remington |
E852850
|
entity |
| Predicate | primaryAntagonistsHunted |
P121133
|
FINISHED |
| Object | man-eating lions |
—
|
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: man-eating lions | Statement: [Charles Remington, primaryAntagonistsHunted, man-eating lions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryAntagonistsHunted Context triple: [Charles Remington, primaryAntagonistsHunted, man-eating lions]
-
A.
primaryAntagonists
Indicates that the referenced entities serve as the main opposing or adversarial forces in relation to a specified subject or narrative.
-
B.
targetOfAntagonists
Indicates that the referenced entity is the object or focus of hostile actions, opposition, or conflict initiated by antagonistic parties.
-
C.
primaryAntagonistSpeciesFaced
chosen
Indicates the species that serves as the main opposing or enemy group confronted by a given entity.
-
D.
primaryAntagonistType
Indicates the role or category of the main opposing force or adversary that serves as the central source of conflict.
-
E.
antagonistOf
Indicates a relationship where one entity actively opposes, conflicts with, or serves as an adversary to another.
- 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_69f349679fd8819093b9b40e989440e3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f338b881908e5593e45d764f4d |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:33 a.m.