Triple
T17710976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turkish tea |
E441563
|
entity |
| Predicate | isRarelyServedWith |
P47543
|
FINISHED |
| Object | milk |
—
|
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: milk | Statement: [Turkish tea, isRarelyServedWith, milk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isRarelyServedWith Context triple: [Turkish tea, isRarelyServedWith, milk]
-
A.
rarelyAppearsWith
chosen
Indicates that one entity is infrequently observed or found together in context, usage, or occurrence with another entity.
-
B.
isTypicallyServedFor
Indicates that one item is most commonly or customarily served as a meal or course for the other (e.g., a dish typically served for breakfast, lunch, or dinner).
-
C.
servesWith
Indicates that one entity is customarily presented, used, or consumed together with another as a complementary accompaniment.
-
D.
servesMostly
Indicates that one entity primarily functions to serve, support, or cater to another entity, more than to any other.
-
E.
servedWith
Indicates that one item is customarily presented, provided, or consumed together with another as an accompaniment or side.
- 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_69d8b9ea20b48190ace88bb46b01e6a9 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4729b5d3c819085613ed25dc6761d |
completed | April 19, 2026, 6:13 a.m. |
| PD | Predicate disambiguation | batch_69e3cde601d4819097903f471f1fe99a |
completed | April 18, 2026, 6:31 p.m. |
Created at: April 10, 2026, 10:05 a.m.