Triple
T37712280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zorro’s Fighting Legion |
E939371
|
entity |
| Predicate | leadCharacterRealIdentity |
P155411
|
FINISHED |
| Object | Don Diego Vega |
—
|
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: Don Diego Vega | Statement: [Zorro’s Fighting Legion, leadCharacterRealIdentity, Don Diego Vega]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadCharacterRealIdentity Context triple: [Zorro’s Fighting Legion, leadCharacterRealIdentity, Don Diego Vega]
-
A.
titleCharacterRealName
chosen
Indicates that a character known by a title or alias has the specified real (personal) name.
-
B.
characterRealWorldCounterpart
Indicates that a fictional character is based on, inspired by, or directly corresponds to a specific real-world person.
-
C.
leadCharacterNickname
Indicates that one entity is the nickname commonly used for the lead (main) character of another entity.
-
D.
rumoredIdentity
Indicates that one entity is believed or speculated to be the identity of another, without confirmed or official verification.
-
E.
characterPortrayedIs
Indicates that one entity serves as the fictional or dramatic role that is depicted or played 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_69f76edb49dc8190b951dce9ce6ef789 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbaef0cec881908c2742d77d145901 |
completed | May 6, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69fbadf632ec8190b14991c971258307 |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:18 p.m.