Triple
T35720455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ben Wood |
E1032455
|
entity |
| Predicate | hasAgeInMainTimeline |
P183858
|
FINISHED |
| Object | adult |
—
|
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: adult | Statement: [Ben Wood, hasAgeInMainTimeline, adult]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAgeInMainTimeline Context triple: [Ben Wood, hasAgeInMainTimeline, adult]
-
A.
ageInSecondaryTimeline
Indicates the age an entity has within an alternate or secondary timeline, distinct from its age in the primary timeline.
-
B.
hasAge
Indicates that an entity possesses a specific age value, typically expressed as a number of time units since its birth or creation.
-
C.
hasAgeSignificance
Indicates that something holds particular importance, relevance, or meaning specifically due to its age or the age of an associated entity.
-
D.
existsInAge
Indicates that an entity is present, valid, or active during a specified age or time period.
-
E.
hasAgeingProtagonist
Indicates that the work features a main character who is experiencing aging or the later stages of life as a central aspect of their role or development.
- 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_69f76e102b5881909e5d63a30a5cecbe |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a34f8ee08190a040304635539a8f |
completed | May 3, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69f7a06f125c8190843af194f042a465 |
completed | May 3, 2026, 7:22 p.m. |
| PDg | Predicate description generation | batch_69f7a34e80dc8190980d5b7b0b91341d |
completed | May 3, 2026, 7:34 p.m. |
Created at: May 3, 2026, 4:05 p.m.