Triple
T35312901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Enterprise (NCC-1701-C) |
E1019823
|
entity |
| Predicate | commandingOfficerDuringNarendra |
P145570
|
FINISHED |
| Object | Captain Rachel Garrett |
—
|
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: Captain Rachel Garrett | Statement: [USS Enterprise (NCC-1701-C), commandingOfficerDuringNarendra, Captain Rachel Garrett]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commandingOfficerDuringNarendra Context triple: [USS Enterprise (NCC-1701-C), commandingOfficerDuringNarendra, Captain Rachel Garrett]
-
A.
commanderIndia
Indicates that the subject serves as a commander associated with India, typically holding a leadership or command role within an Indian military or related organizational context.
-
B.
commandingOfficerDuringEvents
chosen
Indicates that one entity served as the commanding officer of another entity during a specified set of events.
-
C.
wasDirectorGeneralOf
Indicates that a person held the position of Director General of a specified organization or institution.
-
D.
commanderPakistan
Indicates that one entity serves as the military or organizational commander of Pakistan.
-
E.
chiefOfStaff
Indicates that one entity serves as the chief of staff for another entity, typically managing operations and coordinating activities on its behalf.
- 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_69f76de9d45c81908a2ed0956b448b65 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd67191cf88190b53ecbf5be3564e9 |
completed | May 8, 2026, 4:31 a.m. |
| PD | Predicate disambiguation | batch_69fd654fdaac81908e67e75194710f06 |
completed | May 8, 2026, 4:23 a.m. |
Created at: May 3, 2026, 4:03 p.m.