Triple
T33114368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glen |
E847418
|
entity |
| Predicate | hasSiblingPersona |
P193373
|
FINISHED |
| Object | Glenda |
—
|
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: Glenda | Statement: [Glen, hasSiblingPersona, Glenda]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSiblingPersona Context triple: [Glen, hasSiblingPersona, Glenda]
-
A.
hasPersona
Indicates that an entity possesses or is associated with a particular persona, role, or character profile.
-
B.
hasSiblingCollaboration
Indicates a collaborative relationship between two entities that are considered siblings within the same hierarchy or family.
-
C.
hasSiblingMembers
Indicates that two entities are members of a group or organization and are siblings to each other within that membership context.
-
D.
hasSiblingProtagonists
Indicates that the work features two or more protagonists who are siblings to each other.
-
E.
hasSiblingStatus
Indicates that there exists a sibling relationship between two entities, specifying their status as siblings to each other.
- 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_69f3495751a081909850af5843da40dc |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fd44474ed48190ac372e4c88d762ed |
completed | May 8, 2026, 2:02 a.m. |
| PD | Predicate disambiguation | batch_69fd41ef28a48190a66959be5c964461 |
completed | May 8, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69fd4445f8c08190bb2dc27e0971c55d |
completed | May 8, 2026, 2:02 a.m. |
Created at: May 1, 2026, 1:27 a.m.