Triple
T7616292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | C. V. Starr East Asian Library |
E172368
|
entity |
| Predicate | collectsMaterialType |
P78140
|
FINISHED |
| Object | books |
—
|
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: books | Statement: [C. V. Starr East Asian Library, collectsMaterialType, books]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: collectsMaterialType Context triple: [C. V. Starr East Asian Library, collectsMaterialType, books]
-
A.
organizesMaterialType
Indicates that one entity arranges or structures another entity according to a specific type or category of material.
-
B.
hasMaterialType
Indicates that something is composed of, made from, or characterized by a specific type of material.
-
C.
sourceMaterialType
Indicates the type or category of material from which something originates or is derived.
-
D.
featuresMaterialFrom
Indicates that one entity incorporates, contains, or is composed of material originating from another entity.
-
E.
materialUsed
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
- 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_69c6994f50808190ba228764bb422417 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fe73ff7c8190ab1218d97b37416d |
completed | March 27, 2026, 10:02 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e725a88190b1f05dd224f7f4f2 |
completed | March 27, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69c6fe7323b0819081664662d2f26937 |
completed | March 27, 2026, 10:02 p.m. |
Created at: March 27, 2026, 3:55 p.m.