Triple
T5611728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | D-Plan quarter system |
E147372
|
entity |
| Predicate | distinctiveFeatureOf |
P7153
|
FINISHED |
| Object | Dartmouth College identity |
—
|
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: Dartmouth College identity | Statement: [D-Plan quarter system, distinctiveFeatureOf, Dartmouth College identity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distinctiveFeatureOf Context triple: [D-Plan quarter system, distinctiveFeatureOf, Dartmouth College identity]
-
A.
linguisticFeature
Indicates a relationship where a linguistic property, pattern, or characteristic is attributed to or associated with a language-related entity (such as a word, phrase, or text).
-
B.
typicalFeatures
Indicates that the related entities are characteristic or commonly occurring features or attributes of something.
-
C.
languageCharacterizedBy
Indicates that a language is defined or distinguished by a particular feature, property, or characteristic.
-
D.
notableFeatureOn
Indicates that one entity is a prominent or distinguishing feature located on or part of another entity.
-
E.
keyFeature
chosen
Indicates that something is a primary, distinguishing, or most important feature of an entity.
- 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_69c0090500f881908374285baf0ac46f |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0211fad448190b068b77ed25931d5 |
completed | March 22, 2026, 5:04 p.m. |
| PD | Predicate disambiguation | batch_69c01b1b3c98819080687d18ab10a914 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:39 p.m.