Triple
T30897356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Falling In and Out of Love |
E787056
|
entity |
| Predicate | hasIntroductoryRole |
P123788
|
FINISHED |
| Object | intro to Amie |
—
|
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: intro to Amie | Statement: [Falling In and Out of Love, hasIntroductoryRole, intro to Amie]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIntroductoryRole Context triple: [Falling In and Out of Love, hasIntroductoryRole, intro to Amie]
-
A.
hasTrainingRole
Indicates that an entity holds or is assigned a specific role within a training or instructional context.
-
B.
hasIntro
chosen
Indicates that an entity includes or is associated with an introductory section or opening part.
-
C.
hasNotableRoleIn
Indicates that an entity holds a significant or noteworthy role or function within another entity, event, work, or context.
-
D.
hadStaffRole
Indicates that an entity served in a specific staff role or position for another entity during some period.
-
E.
mayHavePriorRole
Indicates that an entity is allowed or expected to have held a specified role at some earlier time.
- 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_69f224bcbcb48190836df847424e4057 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69ff17be6ad48190963206f2619b1b28 |
completed | May 9, 2026, 11:17 a.m. |
| PD | Predicate disambiguation | batch_69ff1724ba24819092c928fcbcb286ec |
completed | May 9, 2026, 11:14 a.m. |
Created at: April 29, 2026, 8:49 p.m.