Triple
T16938173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Clooney as Governor Mike Morris |
E410878
|
entity |
| Predicate | officeHeldInStory |
P102101
|
FINISHED |
| Object | Governor of Pennsylvania |
—
|
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: Governor of Pennsylvania | Statement: [George Clooney as Governor Mike Morris, officeHeldInStory, Governor of Pennsylvania]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHeldInStory Context triple: [George Clooney as Governor Mike Morris, officeHeldInStory, Governor of Pennsylvania]
-
A.
officeHeldInFiction
chosen
Indicates that a particular office, position, or role is held by an entity within a fictional context or work.
-
B.
officeHeldIn
Indicates that a particular office or position is held within or associated with a specific geographic or administrative location.
-
C.
officeHeldDuring
Indicates that a person occupied a specific official position during a particular time period.
-
D.
officeHeldOf
Indicates that a specific office or position is (or was) held by a particular person or entity.
-
E.
officeHeldUnder
Indicates that one entity holds or has held an official position, role, or office under the authority, jurisdiction, or administration of another entity.
- 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_69d886c886688190967be07322597ac9 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cf2b88bc8190aeb7b07032478ae3 |
completed | April 18, 2026, 6:36 p.m. |
| PD | Predicate disambiguation | batch_69e32b9aa8748190b248890aca86753d |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:30 a.m.