Triple
T37109236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porcupine |
E918937
|
entity |
| Predicate | hasProtagonistNickname |
P46224
|
FINISHED |
| Object | Jack |
E14882
|
NE 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: Jack | Statement: [Porcupine, hasProtagonistNickname, Jack]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProtagonistNickname Context triple: [Porcupine, hasProtagonistNickname, Jack]
-
A.
leadCharacterNickname
Indicates that one entity is the nickname commonly used for the lead (main) character of another entity.
-
B.
protagonistAlsoKnownAs
chosen
Indicates that an entity serving as a protagonist is alternatively referred to by another name or alias.
-
C.
propNickname
Indicates that one entity is used as a nickname or informal alternative name for another entity.
-
D.
usesRecurringProtagonistName
Indicates that a work repeatedly features the same protagonist character under a consistent name across multiple installments or stories.
-
E.
protagonistRealWorldName
Indicates that a character’s name in the real world (outside a fictional, virtual, or alternate setting) is associated with that character as the story’s protagonist.
- F. None of above.
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_69f76e9b99c8819096164b21ff5bd996 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a402ba189108190ac703eaddd1dc42f |
completed | June 27, 2026, 7:59 p.m. |
| PD | Predicate disambiguation | batch_6a037a11efc08190bb7cacc1325b4dc6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:14 p.m.