Triple
T36937930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penance |
E913666
|
entity |
| Predicate | firstAppearanceAsPenance |
P106828
|
FINISHED |
| Object | Civil War: Front Line #10 |
E780880
|
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: Civil War: Front Line #10 | Statement: [Penance, firstAppearanceAsPenance, Civil War: Front Line #10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstAppearanceAsPenance Context triple: [Penance, firstAppearanceAsPenance, Civil War: Front Line #10]
-
A.
firstAppearanceAct
Indicates the act in which an entity makes its first appearance within a work or performance.
-
B.
firstAppearancePart
Indicates that an entity makes its first appearance as a component or segment within a larger work or sequence.
-
C.
firstAppearanceMa
Indicates that an entity (such as a character or item) makes its first appearance in a specific manga.
-
D.
firstAppearsAs
chosen
Indicates that an entity is introduced or shown in a particular form, role, or identity for the first time in a given context.
-
E.
firstAppearanceEpisode
Indicates the specific episode in which an entity (such as a character or item) is shown or mentioned for the first time.
- 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_69f76e8a6a5c81909c1febf32bf3fe23 |
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_6a3e163f375c8190849c11ae18ff5e95 |
completed | June 26, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_6a037a10036481909c71188b2a0e7f04 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:13 p.m.