Triple
T7672146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sneezy |
E173772
|
entity |
| Predicate | hasCauseOfSneezing |
P78690
|
FINISHED |
| Object | chronic hay fever (implied) |
—
|
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: chronic hay fever (implied) | Statement: [Sneezy, hasCauseOfSneezing, chronic hay fever (implied)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCauseOfSneezing Context triple: [Sneezy, hasCauseOfSneezing, chronic hay fever (implied)]
-
A.
hasColorOfNose
Indicates that one entity possesses a nose whose color matches or is characterized by the specified color entity.
-
B.
isInhaled
Indicates that one entity is taken into another entity through breathing or suction into an internal space such as lungs or airways.
-
C.
fromNoseCame
Indicates that something originated from or was expelled out of a nose.
-
D.
pollenType
Indicates the specific kind or category of pollen associated with an entity.
-
E.
hasStingingHairs
Indicates that an entity possesses hairs capable of delivering a sting or irritation upon contact.
- F. None of above. chosen
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_69c699562484819086752091e3164a27 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7063dab1881909598b04999b8b690 |
completed | March 27, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69c7015f7430819099d3ea2781b7cee2 |
completed | March 27, 2026, 10:14 p.m. |
| PDg | Predicate description generation | batch_69c7063cfd78819095c6501fe8d57312 |
completed | March 27, 2026, 10:35 p.m. |
Created at: March 27, 2026, 4 p.m.