Triple
T123881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Institute Professor at MIT |
E2504
|
entity |
| Predicate | reservedFor |
P4923
|
FINISHED |
| Object | small number of faculty members |
—
|
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: small number of faculty members | Statement: [Institute Professor at MIT, reservedFor, small number of faculty members]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reservedFor Context triple: [Institute Professor at MIT, reservedFor, small number of faculty members]
-
A.
reserves
Indicates that an entity has arranged in advance to hold or secure something for future use or access.
-
B.
usedFor
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
C.
appointedFor
Indicates that an entity has been officially assigned or designated to perform a specific role, task, or function for another entity or purpose.
-
D.
modernReservation
Indicates that an entity is a contemporary or currently active reservation associated with another entity (such as a group, person, or place).
-
E.
held
Indicates that one entity physically grasped, carried, or kept another entity in its possession or control.
- 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_69a251b54ea88190b18281669f59b4c0 |
completed | Feb. 28, 2026, 2:23 a.m. |
| NER | Named-entity recognition | batch_69a2573ce0ac8190b49fb31d3d475bf9 |
completed | Feb. 28, 2026, 2:47 a.m. |
| PD | Predicate disambiguation | batch_69a2564a54948190ba30bee858173b27 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a256ea776081908fec36c3fdfb8d84 |
completed | Feb. 28, 2026, 2:46 a.m. |
Created at: Feb. 28, 2026, 2:27 a.m.