Triple
T35312905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Enterprise (NCC-1701-C) |
E1019823
|
entity |
| Predicate | temporalPhenomenon |
P1626
|
FINISHED |
| Object | emerged from temporal rift near Enterprise-D |
—
|
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: emerged from temporal rift near Enterprise-D | Statement: [USS Enterprise (NCC-1701-C), temporalPhenomenon, emerged from temporal rift near Enterprise-D]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: temporalPhenomenon Context triple: [USS Enterprise (NCC-1701-C), temporalPhenomenon, emerged from temporal rift near Enterprise-D]
-
A.
temporal
Indicates a relationship that situates one event, state, or entity in time relative to another (e.g., before, after, or during).
-
B.
phenomenon
chosen
Indicates that an entity is a perceptible event, occurrence, or process that can be observed or experienced.
-
C.
temporalEffect
Indicates a relationship where one event, state, or action produces consequences or changes that occur at a later time.
-
D.
temporality
Indicates the time-related relationship between events or states, such as their order, duration, or simultaneity.
-
E.
temporalAspect
Indicates the time-related characteristics or phase (such as duration, frequency, or temporal status) associated with an event or relationship.
- 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_69f7aa699d68819081ed363931894ab3 |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8cec6d48190bebfa884b2f938c0 |
completed | May 3, 2026, 7:58 p.m. |
Created at: May 3, 2026, 4:03 p.m.