Triple
T34978435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poor Miss Finch |
E1008746
|
entity |
| Predicate | hasMedicalMotif |
P160817
|
FINISHED |
| Object | experimental eye surgery |
—
|
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: experimental eye surgery | Statement: [Poor Miss Finch, hasMedicalMotif, experimental eye surgery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMedicalMotif Context triple: [Poor Miss Finch, hasMedicalMotif, experimental eye surgery]
-
A.
medicalConditionAtTime
Indicates that a specified medical condition is present or applicable to an entity during a particular time or time interval.
-
B.
hasAssociatedDisease
Indicates that an entity is linked to, or commonly occurs with, a particular disease or medical condition.
-
C.
hasPossibleSymptom
Indicates that an entity (such as a condition or disease) may be associated with a particular symptom that can potentially occur.
-
D.
hasClinicalFeature
Indicates that an entity (such as a disease, condition, or case) exhibits or is characterized by a particular clinical sign, symptom, or feature.
-
E.
hasHealthCareCharacteristic
chosen
Indicates that an entity possesses a specific healthcare-related attribute, quality, or feature.
- 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_69f76dc844a48190881951fffb83d17e |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff2636e2bc8190bba91eff91431c6e |
completed | May 9, 2026, 12:19 p.m. |
| PD | Predicate disambiguation | batch_69ff25c65be48190868480d94e1c4e89 |
completed | May 9, 2026, 12:17 p.m. |
Created at: May 3, 2026, 4:01 p.m.