Triple
T27936253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Taylor |
E700619
|
entity |
| Predicate | initiallyResents |
P69313
|
FINISHED |
| Object | Forrest Gump |
—
|
NE NERFINISHED |
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: Forrest Gump | Statement: [Daniel Taylor, initiallyResents, Forrest Gump]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: initiallyResents Context triple: [Daniel Taylor, initiallyResents, Forrest Gump]
-
A.
initiallyEnemyOf
Indicates that one entity starts out in a state of enmity or opposition toward another at the beginning of a specified time or situation.
-
B.
initiallyContrastsWith
Indicates that one entity is first presented or perceived in opposition or contrast to another entity at the beginning of a sequence, process, or context.
-
C.
initialAttitude
chosen
Indicates the starting stance, feeling, or disposition one entity holds toward another or toward a situation before any interaction or change occurs.
-
D.
isEmbittered
Indicates that an entity harbors persistent bitterness or resentment, typically as a result of past experiences or perceived wrongs.
-
E.
harborsResentmentToward
Indicates that one entity holds ongoing bitterness, anger, or ill will directed at another entity.
- 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_69ef6a5028108190a14696d9821dde49 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f674e06c9481909ed0ea736408f0d7 |
completed | May 2, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69f673c2f81c8190bf369226306eef09 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 27, 2026, 7:13 p.m.