Triple
T3536279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jennifer Aniston as Dr. Julia Harris |
E74779
|
entity |
| Predicate | targetOfAdvances |
P860
|
FINISHED |
| Object | herDentalAssistant |
—
|
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: herDentalAssistant | Statement: [Jennifer Aniston as Dr. Julia Harris, targetOfAdvances, herDentalAssistant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetOfAdvances Context triple: [Jennifer Aniston as Dr. Julia Harris, targetOfAdvances, herDentalAssistant]
-
A.
target
chosen
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
-
B.
laterGoal
Indicates that one goal occurs or is intended to be achieved after another goal in time.
-
C.
targetOfIntervention
Indicates that an entity is the object or focus upon which an intervention, treatment, or action is directed.
-
D.
victoryTarget
Indicates that one entity is the intended opponent, objective, or condition that must be overcome or achieved for the other entity to attain victory.
-
E.
targetLocation
Indicates the specific place or destination toward which an action, movement, or effect is directed.
- 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_69ad85d1a3948190931fd1ea1f49717b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbcc7b92481908d2d99948780f4d0 |
completed | March 8, 2026, 6:15 p.m. |
| PD | Predicate disambiguation | batch_69adae13ab808190a5d6ecdc7543445e |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:20 p.m.