Triple
T19695115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Million-Year Picnic |
E472935
|
entity |
| Predicate | hasTitleCharacterAction |
P136953
|
FINISHED |
| Object | family chooses to become the new Martians |
—
|
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: family chooses to become the new Martians | Statement: [The Million-Year Picnic, hasTitleCharacterAction, family chooses to become the new Martians]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleCharacterAction Context triple: [The Million-Year Picnic, hasTitleCharacterAction, family chooses to become the new Martians]
-
A.
hasTitleLetter
Indicates that an entity possesses a specific letter or character within its title.
-
B.
hasMainTitleCharacter
Indicates that a work’s primary or main title is centered on, derived from, or explicitly names a particular character.
-
C.
hasTitleCharacterLocation
Indicates that a title or heading is associated with a specific character’s location within a text or media.
-
D.
hasTitleIn
Indicates that an entity holds or is associated with a specific title within a particular context, domain, or language.
-
E.
hasTitleCharacterTrait
Indicates that a title is associated with a specific character trait of an entity.
- 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_69d8e515bef88190bc30781aea50537a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e642147c3c8190a4c788e4bb48fe11 |
completed | April 20, 2026, 3:11 p.m. |
| PD | Predicate disambiguation | batch_69e53039ea808190a9106a53f564ab92 |
completed | April 19, 2026, 7:42 p.m. |
| PDg | Predicate description generation | batch_69e532bbedf081908d801600e2af94a7 |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 1:46 p.m.