Triple
T25194119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | "No Sanctuary" |
E630955
|
entity |
| Predicate | featuresFlashback |
P169512
|
FINISHED |
| Object | origin of Terminus |
—
|
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: origin of Terminus | Statement: ["No Sanctuary", featuresFlashback, origin of Terminus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresFlashback Context triple: ["No Sanctuary", featuresFlashback, origin of Terminus]
-
A.
featuresHistorian
Indicates that something includes or presents a historian as a notable participant, subject, or element.
-
B.
featuresReturnOf
Indicates that something (such as a work, event, or product) includes or highlights the comeback or reappearance of a person, character, element, or feature.
-
C.
featuresReimaginedVersionOf
Indicates that something includes or presents a newly interpreted or updated version of another existing work or element.
-
D.
featuresTimeline
Indicates that something presents or includes a chronological sequence of events or developments.
-
E.
featuresStar
Indicates that one entity prominently includes or showcases another entity as a main star or featured performer.
- F. None of above. chosen
Provenance (4 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_69e75a8a6d088190ba1e82a4345225e7 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f67fc237608190b6542b56038a7fe4 |
completed | May 2, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69f67e3ed894819094c067c1ef624951 |
completed | May 2, 2026, 10:44 p.m. |
| PDg | Predicate description generation | batch_69f67f0353c88190a05b2db449abe0f4 |
completed | May 2, 2026, 10:47 p.m. |
Created at: April 21, 2026, 12:45 p.m.