Triple
T29188219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Legacy era |
E739926
|
entity |
| Predicate | timelineStatus |
P43503
|
FINISHED |
| Object | non-canon under current Star Wars continuity |
—
|
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: non-canon under current Star Wars continuity | Statement: [Legacy era, timelineStatus, non-canon under current Star Wars continuity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timelineStatus Context triple: [Legacy era, timelineStatus, non-canon under current Star Wars continuity]
-
A.
timelineDetail
Indicates a detailed view or breakdown of events, actions, or states along a timeline associated with an entity or process.
-
B.
timelineUse
Indicates that one entity utilizes or incorporates another entity within a temporal sequence or schedule (a timeline).
-
C.
statusPeriod
Indicates the time interval during which a particular status or condition is in effect.
-
D.
timeStatus
chosen
Indicates the temporal state or condition of an event or entity relative to a reference time (e.g., past, present, future, ongoing, or scheduled).
-
E.
targetsStatus
Indicates that one entity directs its actions or focus toward another entity based on the latter’s current status or condition.
- 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_69f07cb8033c8190b8807e219a14333d |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f66388afe48190a68caf56c9745007 |
completed | May 2, 2026, 8:50 p.m. |
| PD | Predicate disambiguation | batch_69f65c24f8b48190af81b575f3c15be5 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, 12:01 p.m.