Triple
T32553149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zion |
E832024
|
entity |
| Predicate | statusByEndOfTrilogy |
P83430
|
FINISHED |
| Object | survives after truce between humans and machines |
—
|
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: survives after truce between humans and machines | Statement: [Zion, statusByEndOfTrilogy, survives after truce between humans and machines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statusByEndOfTrilogy Context triple: [Zion, statusByEndOfTrilogy, survives after truce between humans and machines]
-
A.
concludesTrilogy
Indicates that the subject work serves as the final installment completing a trilogy that began with the related earlier works.
-
B.
statusDuringSequelTrilogy
Indicates the condition or state of an entity specifically during the time period covered by the sequel trilogy.
-
C.
hasTrilogy
Indicates that an entity is part of, or associated with, a specific trilogy within a larger set of works or narratives.
-
D.
statusAtEndOfFilm
chosen
Indicates the condition or situation an entity is in when the film concludes.
-
E.
trilogyDepicts
Indicates that a trilogy portrays, represents, or narratively focuses on a particular subject, event, or set of entities.
- 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_69f34926b9848190ace47d2dd0a0de7c |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fea5e828cc8190a9b755a645dc56d2 |
completed | May 9, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69fea36443f08190b2aced9b4a0525fd |
completed | May 9, 2026, 3 a.m. |
Created at: May 1, 2026, 1:02 a.m.