Triple
T33594899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Heggen |
E860532
|
entity |
| Predicate | basedOnExperienceFor |
P88172
|
FINISHED |
| Object | Mister Roberts |
—
|
NE NERFINISHED |
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: Mister Roberts | Statement: [Thomas Heggen, basedOnExperienceFor, Mister Roberts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnExperienceFor Context triple: [Thomas Heggen, basedOnExperienceFor, Mister Roberts]
-
A.
basedOnExperience
Indicates that something is determined, chosen, or formed according to prior experience or experiential knowledge.
-
B.
basedOnCareerOf
chosen
Indicates that something (such as a work, character, or storyline) is derived from, inspired by, or modeled on the career or professional life of a particular person.
-
C.
basedOnExpertiseOf
Indicates that something is determined, derived, or justified using the knowledge, skills, or judgment of a particular expert or group of experts.
-
D.
usedExperienceIn
Indicates that an entity applied or leveraged a particular experience or expertise in performing an action or achieving a result.
-
E.
comparesExperienceTo
Indicates that one entity evaluates or contrasts the level, amount, or quality of experience of one entity with that of another.
- 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_69f3497f35908190a2e9bbb9b96c7a3f |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fec25f0fc48190b87ab1f9cd1eb0de |
completed | May 9, 2026, 5:13 a.m. |
| PD | Predicate disambiguation | batch_69fec079a770819098df7cc3049df954 |
completed | May 9, 2026, 5:04 a.m. |
Created at: May 1, 2026, 1:41 a.m.