Triple
T2466911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valmur |
E55271
|
entity |
| Predicate | servingSuggestion |
P11944
|
FINISHED |
| Object | pairs well with seafood |
—
|
LITERAL 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: pairs well with seafood | Statement: [Valmur, servingSuggestion, pairs well with seafood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servingSuggestion Context triple: [Valmur, servingSuggestion, pairs well with seafood]
-
A.
alsoServes
Indicates that an entity, in addition to its primary role or function, provides service or support to another specified entity or group.
-
B.
servedWith
chosen
Indicates that one item is customarily presented, provided, or consumed together with another as an accompaniment or side.
-
C.
intendedToServe
Indicates that one entity was designed, planned, or purposed specifically to benefit, assist, or fulfill the needs of another entity.
-
D.
offersMeal
Indicates that one entity provides or makes available a meal to another entity.
-
E.
servesMostly
Indicates that one entity primarily functions to serve, support, or cater to another entity, more than to any other.
- 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_69ab49e3622c8190ad22afa2c4fbb807 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd2bc7b5481908b3664495e99f1a4 |
completed | March 7, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69abd0b3ea308190a6d8499c2a542c50 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:44 p.m.