Triple
T36599917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peyer’s patches |
E902888
|
entity |
| Predicate | roleInVaccineResponse |
P203558
|
FINISHED |
| Object | target for oral vaccines |
—
|
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: target for oral vaccines | Statement: [Peyer’s patches, roleInVaccineResponse, target for oral vaccines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInVaccineResponse Context triple: [Peyer’s patches, roleInVaccineResponse, target for oral vaccines]
-
A.
roleInAppointments
Indicates the specific function or capacity an entity holds within one or more scheduled appointments.
-
B.
roleInRepertoire
Indicates that an entity serves a specific role or function within a larger repertoire, collection, or set of items.
-
C.
roleInvolves
Indicates that a particular role includes or requires participation in a specified activity, responsibility, or function.
-
D.
roleInName
Indicates that a specific role, title, or position is included as part of an entity’s name or naming expression.
-
E.
roleAtGV
Indicates that an entity holds or held a specific role or position at a particular organization, institution, or venue referred to as GV.
- 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_69f76e66b7b88190848f7a3e1188915f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a01a23d8b148190ac2c8765aa9227c4 |
completed | May 11, 2026, 9:32 a.m. |
| PD | Predicate disambiguation | batch_6a01a1e8bb90819096647e929bfb3db8 |
completed | May 11, 2026, 9:31 a.m. |
| PDg | Predicate description generation | batch_6a01a23ce3b08190acb03793824baf68 |
completed | May 11, 2026, 9:32 a.m. |
Created at: May 3, 2026, 4:11 p.m.