Triple
T32117229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacob Batalon |
E820270
|
entity |
| Predicate | portraysFriendOfCharacter |
P118005
|
FINISHED |
| Object | Peter Parker |
—
|
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: Peter Parker | Statement: [Jacob Batalon, portraysFriendOfCharacter, Peter Parker]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysFriendOfCharacter Context triple: [Jacob Batalon, portraysFriendOfCharacter, Peter Parker]
-
A.
portraysCharacterRelationship
Indicates that one entity depicts or represents the relationship between characters in another entity.
-
B.
friendPortrayedBy
chosen
Indicates that a person’s friend is depicted or represented by a particular actor or performer.
-
C.
portraysRelationshipWith
Indicates that one entity depicts, represents, or characterizes another entity as being in a specific kind of relationship with it or with a third party.
-
D.
portraysFictionalEntity
Indicates that one entity depicts, represents, or plays the role of a fictional character or figure.
-
E.
portraysRelationship
Indicates that one entity depicts, represents, or illustrates a relationship between other entities.
- 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_69f3490209c881908ec0241476715f15 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fe1fd637c08190aa95cd2478c278cb |
completed | May 8, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69fe19344bb481909b5e2144155e4add |
completed | May 8, 2026, 5:11 p.m. |
Created at: May 1, 2026, 12:28 a.m.