Triple
T31355171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LVPD Homicide |
E799708
|
entity |
| Predicate | hasFictionalCommanderRole |
P67496
|
FINISHED |
| Object | homicide lieutenant |
—
|
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: homicide lieutenant | Statement: [LVPD Homicide, hasFictionalCommanderRole, homicide lieutenant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalCommanderRole Context triple: [LVPD Homicide, hasFictionalCommanderRole, homicide lieutenant]
-
A.
hasFictionalLeader
chosen
Indicates that an entity is led or governed by a leader who is a fictional character rather than a real person.
-
B.
RepublicanCommander
Indicates that an individual serves as a military commander for the Republican side in a conflict.
-
C.
hasCommanderRank
Indicates that an entity holds the military or organizational rank of commander within a specified hierarchy or context.
-
D.
hasCommander
Indicates that one entity serves as the commanding officer or leader of another entity.
-
E.
roleInRogueOne
Indicates that an entity has a specific acting or production role in the film "Rogue One: A Star Wars Story."
- 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_69f224e5e9bc8190a16339328897c4f8 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe78e545888190a239af1a84280fa0 |
completed | May 8, 2026, 11:59 p.m. |
| PD | Predicate disambiguation | batch_69fe7842742081908043eb950ed69f92 |
completed | May 8, 2026, 11:56 p.m. |
Created at: April 29, 2026, 9:17 p.m.