Triple
T36420599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cecil Parker |
E897143
|
entity |
| Predicate | hasLastNameInCareer |
P200832
|
FINISHED |
| Object | Parker |
—
|
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: Parker | Statement: [Cecil Parker, hasLastNameInCareer, Parker]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLastNameInCareer Context triple: [Cecil Parker, hasLastNameInCareer, Parker]
-
A.
hasLastNameInWork
Indicates that a person or character is referred to by a specific last name within a particular work (e.g., book, film, or other creative piece).
-
B.
hasNotableSurname
Indicates that an entity bears a surname that is recognized as notable, distinguished, or of particular significance.
-
C.
hasSeptSurname
Indicates that an entity bears a surname associated with a particular sept (a family subgroup or clan division).
-
D.
isOccupationalSurname
Indicates that a surname originates from or is derived from a person’s occupation or trade.
-
E.
hasNotablePersonWithSurname
Indicates that an entity is associated with at least one notable person who bears a specified surname.
- 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_69f76e559b10819099d6655a6e14587c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ffb1218cb08190a814c7f0833501a7 |
completed | May 9, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69ffb083d6988190b2757e0cfd629b75 |
completed | May 9, 2026, 10:09 p.m. |
| PDg | Predicate description generation | batch_69ffb120b9988190b6361c69265033c0 |
completed | May 9, 2026, 10:11 p.m. |
Created at: May 3, 2026, 4:10 p.m.