Triple
T36079139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Betty Broderick |
E1043589
|
entity |
| Predicate | victimOfCrimeCommittedByHer |
P50002
|
FINISHED |
| Object | Daniel T. Broderick III |
—
|
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: Daniel T. Broderick III | Statement: [Betty Broderick, victimOfCrimeCommittedByHer, Daniel T. Broderick III]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: victimOfCrimeCommittedByHer Context triple: [Betty Broderick, victimOfCrimeCommittedByHer, Daniel T. Broderick III]
-
A.
portraysAsVictim
Indicates that one entity represents or depicts another entity as a victim in a given context or narrative.
-
B.
allegedVictimOf
Indicates that one entity is claimed or reported to have been harmed, wronged, or victimized by another entity, without asserting that the claim is proven.
-
C.
victimWas
Indicates that one entity was the victim of an action, event, or harmful behavior carried out by another entity.
-
D.
victimOfAccusation
Indicates that an entity is the target or subject of an accusation made by another party.
-
E.
isVictimOf
chosen
Indicates that one entity suffers harm, loss, or wrongdoing as a result of another entity’s actions or events.
- 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_69f76e3154908190a6f702671c2bea08 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b2c771108190adeec151daad5dab |
completed | May 3, 2026, 8:40 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bad2e88190963ab4ee5d4f2038 |
completed | May 3, 2026, 8:36 p.m. |
Created at: May 3, 2026, 4:08 p.m.