Triple
T5401414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daily Bugle newsroom |
E120785
|
entity |
| Predicate | associatedWithCharacterRole |
P63755
|
FINISHED |
| Object | Peter Parker's workplace |
—
|
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: Peter Parker's workplace | Statement: [Daily Bugle newsroom, associatedWithCharacterRole, Peter Parker's workplace]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithCharacterRole Context triple: [Daily Bugle newsroom, associatedWithCharacterRole, Peter Parker's workplace]
-
A.
associatedWithCharacterGroup
Indicates that an entity has a connection or affiliation with a particular group of characters.
-
B.
actorRole
Indicates that an entity participates in an event or action in a specific capacity or function (such as performer, initiator, or responsible party).
-
C.
relatedCharacter
Indicates that one character has a specified relationship or association with another character.
-
D.
appearsWithCharacter
Indicates that two characters are shown or present together within the same scene, shot, or context.
-
E.
actingRoleType
Indicates the specific type or category of role an entity performs when acting in a particular capacity or function.
- 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_69bd46391c0c81909fa484446732b6a3 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8932b8bc8190bd31e11b167a7212 |
completed | March 20, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_69bd84660ea08190a641084814fcf94d |
completed | March 20, 2026, 5:31 p.m. |
| PDg | Predicate description generation | batch_69bd8931302c81908afcb0f011e91f09 |
completed | March 20, 2026, 5:51 p.m. |
Created at: March 20, 2026, 2:04 p.m.