Triple
T10210053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clarisse McClellan |
E242301
|
entity |
| Predicate | firstMeetsProtagonistWhile |
P58222
|
FINISHED |
| Object | walking home from work |
—
|
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: walking home from work | Statement: [Clarisse McClellan, firstMeetsProtagonistWhile, walking home from work]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstMeetsProtagonistWhile Context triple: [Clarisse McClellan, firstMeetsProtagonistWhile, walking home from work]
-
A.
firstMeets
chosen
Indicates that one entity encounters or comes into contact with another entity for the first time.
-
B.
firstMeetingPlace
Indicates the location where two or more entities met each other for the very first time.
-
C.
firstMeetingSeason
Indicates the season of the year during which two entities first met.
-
D.
mainProtagonist
Indicates that the subject is the central character or primary focus in the narrative of the related work.
-
E.
firstMission
Indicates that an entity is undertaking or associated with its initial mission or assignment in a given context.
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa22071c819095febd18dd607978 |
completed | April 6, 2026, 12:42 p.m. |
| PD | Predicate disambiguation | batch_69d39559e5ac8190b88eca75956b7e6a |
completed | April 6, 2026, 11:13 a.m. |
Created at: April 6, 2026, 11:01 a.m.