Triple
T19549786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | María de la Luz Cervantes |
E489165
|
entity |
| Predicate | primaryMotivationAtStart |
P78649
|
FINISHED |
| Object | to make a phone call |
—
|
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: to make a phone call | Statement: [María de la Luz Cervantes, primaryMotivationAtStart, to make a phone call]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryMotivationAtStart Context triple: [María de la Luz Cervantes, primaryMotivationAtStart, to make a phone call]
-
A.
motivationFor
Indicates that one entity serves as the reason, drive, or incentive behind another entity’s action, state, or occurrence.
-
B.
laterMotivation
Indicates that one event, state, or action serves as a motivation or reason for another event, state, or action that occurs later in time.
-
C.
motivatedByGoal
Indicates that an action, behavior, or state occurs as a result of an intention to achieve a specific goal or desired outcome.
-
D.
primaryMotif
Indicates that one entity serves as the main recurring theme or dominant motif associated with another entity.
-
E.
primaryIntent
chosen
Indicates the main purpose, goal, or motivation underlying an action, event, or relationship among 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63d2f39188190976e8b6b111499a0 |
completed | April 20, 2026, 2:50 p.m. |
| PD | Predicate disambiguation | batch_69e514d4df3c8190b7e9b3b4fdf9452a |
completed | April 19, 2026, 5:45 p.m. |
Created at: April 10, 2026, 1:41 p.m.