Triple
T10842914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tangierine Café |
E255932
|
entity |
| Predicate | hasCounterOrdering |
P88387
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Tangierine Café, hasCounterOrdering, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCounterOrdering Context triple: [Tangierine Café, hasCounterOrdering, yes]
-
A.
hasOrderingMethod
chosen
Indicates that there is a specific method or procedure used to place or arrange an order for something.
-
B.
hasRankOrder
Indicates that one entity is ordered or positioned relative to others according to a specific ranking or sequence.
-
C.
hasElementOrdersUpTo
Indicates that one entity includes or supports elements whose orders (e.g., magnitudes, degrees, or hierarchical levels) do not exceed a specified upper limit defined by the other entity.
-
D.
hasOrder
Indicates that one entity possesses, is associated with, or is characterized by a specific order, sequence, or arrangement relative to others.
-
E.
hasCheckoutCounter
Indicates that one entity possesses or includes a checkout counter used for processing purchases or transactions.
- 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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d750ce40108190895c477553195fe4 |
completed | April 9, 2026, 7:10 a.m. |
| PD | Predicate disambiguation | batch_69d70d25280c8190b648d7d1958b413a |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:19 p.m.