Triple
T37798230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ellie Burr |
E942293
|
entity |
| Predicate | hasProfessionalRoleModel |
P204390
|
FINISHED |
| Object | Will Dormer |
E258360
|
NE 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: Will Dormer | Statement: [Ellie Burr, hasProfessionalRoleModel, Will Dormer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProfessionalRoleModel Context triple: [Ellie Burr, hasProfessionalRoleModel, Will Dormer]
-
A.
hasProfessionalStatus
Indicates that an entity holds a particular professional standing, rank, or qualification within a field or occupation.
-
B.
hasProfessionalSection
Indicates that an entity includes or is associated with a designated professional section, division, or category within its structure or content.
-
C.
hasProfessionSetting
Indicates that an entity’s professional activity or role is carried out within a particular setting or environment.
-
D.
hasProfessionalComponent
Indicates that something includes, involves, or is associated with a professional (work- or career-related) element or aspect.
-
E.
hasGivenProfession
Indicates that an entity holds or practices a specified profession or occupation.
- F. None of above. chosen
Provenance (5 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_69f76ee6f1f4819091e2cf9c9e6aee19 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a412c99739c8190a1c78e1fcceb755b |
completed | June 28, 2026, 2:15 p.m. |
| PD | Predicate disambiguation | batch_6a037a1772e48190ba738c6d11b321e2 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c84ecbc81908232e5215355f43b |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:19 p.m.