Triple
T31965153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ensign Flandry |
E816154
|
entity |
| Predicate | characterRoleOfDominicFlandry |
P197598
|
FINISHED |
| Object | young intelligence officer |
—
|
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: young intelligence officer | Statement: [Ensign Flandry, characterRoleOfDominicFlandry, young intelligence officer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterRoleOfDominicFlandry Context triple: [Ensign Flandry, characterRoleOfDominicFlandry, young intelligence officer]
-
A.
characterPlayedByJamieDornan
Indicates that the subject is a character portrayed by the actor Jamie Dornan.
-
B.
characterPlayedByNicholasHamilton
Indicates that the subject is a character portrayed by the actor Nicholas Hamilton.
-
C.
characterPortrayedByFrancisLSullivan
Indicates that a character is portrayed or played by the actor Francis L. Sullivan.
-
D.
roleInTheAdventuresOfFordFairlane
Indicates that an entity has a specific role or appearance in the film "The Adventures of Ford Fairlane."
-
E.
characterPlayedByRichardHarris
Indicates that the subject is a character that was portrayed by the actor Richard Harris.
- F. None of above. chosen
Provenance (4 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_69f348f5ae5481909da0247869f51955 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fe9dfaa2d08190b2084f63f842eb6b |
completed | May 9, 2026, 2:37 a.m. |
| PD | Predicate disambiguation | batch_69fe9bba947c81908b0b2b92a4d19b37 |
completed | May 9, 2026, 2:28 a.m. |
| PDg | Predicate description generation | batch_69fe9df9561c8190a068f91c9fc78e56 |
completed | May 9, 2026, 2:37 a.m. |
Created at: May 1, 2026, 12:09 a.m.