Triple
T38604688
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LTI Gray Matter |
E934309
|
entity |
| Predicate | hasNotableLicensedFranchise |
P192903
|
FINISHED |
| Object | Marvel Comics |
E57939
|
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: Marvel Comics | Statement: [LTI Gray Matter, hasNotableLicensedFranchise, Marvel Comics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableLicensedFranchise Context triple: [LTI Gray Matter, hasNotableLicensedFranchise, Marvel Comics]
-
A.
hasNotableFranchise
Indicates that an entity is associated with a well-known, significant, or widely recognized franchise.
-
B.
hasNotableFranchisePartner
Indicates that an entity has a significant or prominent partner involved in a franchise relationship with it.
-
C.
hasMainFranchise
Indicates that an entity is associated with or belongs to a primary or central franchise within a broader set of related works or brands.
-
D.
includesFranchisesAffiliatedWith
Indicates that one entity contains or encompasses franchises that are formally affiliated with another entity.
-
E.
includesFranchisesFrom
chosen
Indicates that one entity contains or encompasses franchises that originate from another entity.
- 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_69f76ecc17688190b389b693a5927501 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a41eaa85d308190b74e95c3f174c698 |
completed | June 29, 2026, 3:46 a.m. |
| PD | Predicate disambiguation | batch_6a037a2026248190b894436a578d79ac |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:32 p.m.