Triple
T29138299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dimmsdale |
E738561
|
entity |
| Predicate | hasLeaderInFiction |
P127989
|
FINISHED |
| Object | Mayor of Dimmsdale |
—
|
NE NERFINISHED |
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: Mayor of Dimmsdale | Statement: [Dimmsdale, hasLeaderInFiction, Mayor of Dimmsdale]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLeaderInFiction Context triple: [Dimmsdale, hasLeaderInFiction, Mayor of Dimmsdale]
-
A.
hasFictionalLeader
Indicates that an entity is led or governed by a leader who is a fictional character rather than a real person.
-
B.
hasLeaderInStory
chosen
Indicates that one entity serves as the leader of another entity within the context of a specific story or narrative.
-
C.
hasFictionalAuthor
Indicates that one entity is the fictional or in-universe author of a work attributed to them.
-
D.
hasRankInFiction
Indicates that a fictional character or entity holds a specific rank, title, or hierarchical position within a fictional context or universe.
-
E.
hasFictionalAutobiographer
Indicates that an entity is associated with a fictional character who serves as its autobiographical narrator or self-describing author within a narrative.
- 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_69f07cb3adb48190a9e0e169cd026634 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f7817daf00819098936402e75ab0a6 |
completed | May 3, 2026, 5:10 p.m. |
| PD | Predicate disambiguation | batch_69f780fc5ed88190b7200ee5a29940af |
completed | May 3, 2026, 5:08 p.m. |
Created at: April 28, 2026, 11:35 a.m.