Triple
T17909856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Exit 9B |
E447792
|
entity |
| Predicate | featuresManyPastCharacters |
P129270
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Exit 9B, featuresManyPastCharacters, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresManyPastCharacters Context triple: [Exit 9B, featuresManyPastCharacters, true]
-
A.
featuresCharactersFrom
Indicates that one entity (such as a work or production) includes or presents characters originating from another entity.
-
B.
formerCharacter
Indicates that an entity was once a character in a work or series but is no longer an active or current character.
-
C.
associatedCharacters
Indicates that two or more characters are linked or connected through some relationship, involvement, or relevance to each other.
-
D.
featuresCharacterWith
Indicates that one entity (such as a work or product) includes or presents a particular character as part of its content.
-
E.
characters
Indicates that one entity is a character (or set of characters) associated with, appearing in, or belonging to another entity (such as a work, story, or medium).
- 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49e9f4f888190840c8b55672becf8 |
completed | April 19, 2026, 9:21 a.m. |
| PD | Predicate disambiguation | batch_69e3d8ec2f6881909d7f54b878cbed37 |
completed | April 18, 2026, 7:18 p.m. |
| PDg | Predicate description generation | batch_69e3db77df0c819084548168c62b398c |
completed | April 18, 2026, 7:28 p.m. |
Created at: April 10, 2026, 10:19 a.m.