Triple
T21813350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | former Solvay Institute of Pharmacology |
E538531
|
entity |
| Predicate | hasPreviousFunction |
P145756
|
FINISHED |
| Object | pharmacology institute |
—
|
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: pharmacology institute | Statement: [former Solvay Institute of Pharmacology, hasPreviousFunction, pharmacology institute]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPreviousFunction Context triple: [former Solvay Institute of Pharmacology, hasPreviousFunction, pharmacology institute]
-
A.
hasPreviousHolder
Indicates that an entity was formerly held, occupied, or possessed by another specified entity before the current one.
-
B.
hasPreviousProduct
Indicates that an entity is linked to another entity that came immediately before it in a sequence of products.
-
C.
hasPrecedingCondition
Indicates that one condition occurs or exists before another condition in time or sequence.
-
D.
hasPredecessorMP
Indicates that one member of parliament previously held the same parliamentary position or seat before another member of parliament.
-
E.
hasSubsequent
Indicates that one entity occurs, appears, or is positioned after another in a defined sequence or order.
- 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_69e0c473f0f8819086c9d1b4a143bd67 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f07cc7ec1c8190a5420b44a49ae32f |
completed | April 28, 2026, 9:24 a.m. |
| PD | Predicate disambiguation | batch_69e6be815a108190be81d7c987d0c0d6 |
completed | April 21, 2026, 12:02 a.m. |
| PDg | Predicate description generation | batch_69e6c670ee608190b9cfdc09de74f0de |
completed | April 21, 2026, 12:36 a.m. |
Created at: April 16, 2026, 6:54 p.m.