Triple
T9828483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Department of Modern Languages and Literatures |
E238719
|
entity |
| Predicate | hasSubfields |
P28231
|
FINISHED |
| Object | linguistics |
—
|
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: linguistics | Statement: [Department of Modern Languages and Literatures, hasSubfields, linguistics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubfields Context triple: [Department of Modern Languages and Literatures, hasSubfields, linguistics]
-
A.
hasSubfieldGroup
Indicates that an entity includes or is associated with a specific subgroup of related subfields within its overall structure or domain.
-
B.
containsAsSubfield
chosen
Indicates that one field or data structure includes another field as a nested or component subfield within it.
-
C.
hasSubunits
Indicates that an entity is composed of or organized into smaller constituent units that are part of its structure.
-
D.
hasSubSeries
Indicates that one series is a subordinate or component series within a larger parent series.
-
E.
hasSubConcept
Indicates that one concept is a more specific, subordinate, or narrower idea within the scope of another, more general concept.
- 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_69ca84e0dd1881909800765d1e21f735 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3268fcc8190b7a028f224512e5f |
completed | April 2, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69cd03e30bc08190816c0a6d29c21b0f |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:32 p.m.