Triple
T5420736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One Fish, Two Fish, Red Fish, Blue Fish |
E121240
|
entity |
| Predicate | hasQueueDecor |
P38145
|
FINISHED |
| Object | Seuss-style graphics and colors |
—
|
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: Seuss-style graphics and colors | Statement: [One Fish, Two Fish, Red Fish, Blue Fish, hasQueueDecor, Seuss-style graphics and colors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasQueueDecor Context triple: [One Fish, Two Fish, Red Fish, Blue Fish, hasQueueDecor, Seuss-style graphics and colors]
-
A.
hasQueue
Indicates that an entity maintains or is associated with a queue, typically representing an ordered list of items or tasks awaiting processing.
-
B.
hasQueueType
Indicates that an entity is associated with a specific type or category of queue.
-
C.
hasDecor
chosen
Indicates that one entity possesses, features, or is adorned with a particular decorative element or style.
-
D.
hasQueueEntertainment
Indicates that an entity provides or features entertainment specifically for people waiting in a queue.
-
E.
hasWaitingArea
Indicates that an entity provides or includes a designated space where people can wait before receiving a service or proceeding to another area.
- 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_69bd463b58d88190b258261573de9e91 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd87eac41481908a4982db5d119edd |
completed | March 20, 2026, 5:46 p.m. |
| PD | Predicate disambiguation | batch_69bd8469f5e48190bbe5c8bdfe8925ea |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:06 p.m.