Triple
T32485689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tammy Gregorio |
E830233
|
entity |
| Predicate | franchiseEntryOf |
P53123
|
FINISHED |
| Object | NCIS |
—
|
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: NCIS | Statement: [Tammy Gregorio, franchiseEntryOf, NCIS]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: franchiseEntryOf Context triple: [Tammy Gregorio, franchiseEntryOf, NCIS]
-
A.
franchiseEntryNumber
Indicates the ordinal position or sequence number of an entry within a franchise series.
-
B.
franchiseEntryType
Indicates the specific category or type of entry by which a franchise participates or is represented within a larger system or context.
-
C.
franchiseElement
chosen
Indicates that one entity is a component, installment, or part within a larger franchise or series associated with another entity.
-
D.
participatingFranchise
Indicates that a franchise is involved as a participant in a particular program, event, or arrangement.
-
E.
franchiseOf
Indicates that one entity operates as a franchise belonging to or licensed by another entity.
- 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_69f34920aa4081908d8fb0277414b911 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6d74b20a48190900dda1014cc13a8 |
completed | May 3, 2026, 5:04 a.m. |
| PD | Predicate disambiguation | batch_69f6d26f27dc8190ae426a3e1573933e |
completed | May 3, 2026, 4:43 a.m. |
Created at: May 1, 2026, 12:58 a.m.