Triple
T35312903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Enterprise (NCC-1701-C) |
E1019823
|
entity |
| Predicate | crewComplementStatusAtNarendra |
P51184
|
FINISHED |
| Object | heavily damaged and many casualties |
—
|
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: heavily damaged and many casualties | Statement: [USS Enterprise (NCC-1701-C), crewComplementStatusAtNarendra, heavily damaged and many casualties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crewComplementStatusAtNarendra Context triple: [USS Enterprise (NCC-1701-C), crewComplementStatusAtNarendra, heavily damaged and many casualties]
-
A.
crewComplementStatusOnLaunch
Indicates the status or condition of a vehicle’s assigned crew complement at the moment of launch.
-
B.
crewOnboard
Indicates that a person or group is serving as crew aboard a specific vehicle, vessel, or craft.
-
C.
crewStatus
chosen
Indicates the current operational or role-related condition of a crew member or crew group within a mission or organization.
-
D.
totalCrewMembers
Indicates the total number of crew members associated with a given entity or context.
-
E.
crewComplementType
Indicates the classification or category of a crew complement associated with an entity (such as its role, composition, or staffing type).
- 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_69f79da9f80c8190b0afd8509f28747b |
completed | May 3, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_69f79617d40481909ba372f94209c08b |
completed | May 3, 2026, 6:38 p.m. |
Created at: May 3, 2026, 4:03 p.m.