Triple
T33771490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poppy Land |
E865392
|
entity |
| Predicate | hasNotableSceneWithCharacter |
P128577
|
FINISHED |
| Object | Eggsy Unwin |
E49510
|
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: Eggsy Unwin | Statement: [Poppy Land, hasNotableSceneWithCharacter, Eggsy Unwin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableSceneWithCharacter Context triple: [Poppy Land, hasNotableSceneWithCharacter, Eggsy Unwin]
-
A.
notableScene
Indicates that a particular scene is especially significant, memorable, or noteworthy within a work or context.
-
B.
notableSceneAssociation
chosen
Indicates an association between an entity and a notable or memorable scene in which it prominently appears or plays a significant role.
-
C.
hasNotableCharacterDynamic
Indicates that there is a particularly distinctive, memorable, or significant pattern of interaction or relationship between the involved characters.
-
D.
hasCharacterMonologue
Indicates that a character delivers an extended solo speech or monologue within a narrative or performance.
-
E.
hasCastCharacter
Indicates that a media work includes a specific character as part of its cast.
- 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_69f3498df6f88190bf9647ea4e4a956e |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a0204dafcc08190868a6f3eab162505 |
completed | May 11, 2026, 4:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a366e89c4608190ad48be6e2a48d826 |
completed | June 20, 2026, 10:42 a.m. |
| PD | Predicate disambiguation | batch_6a0202dc60348190a140bb9da906f5b6 |
completed | May 11, 2026, 4:25 p.m. |
Created at: May 1, 2026, 1:45 a.m.