Triple
T26780693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M.G.L. |
E670237
|
entity |
| Predicate | typicalCitationExample |
P22441
|
FINISHED |
| Object | "G.L. c. 93A" or "M.G.L. c. 93A" |
—
|
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: "G.L. c. 93A" or "M.G.L. c. 93A" | Statement: [M.G.L., typicalCitationExample, "G.L. c. 93A" or "M.G.L. c. 93A"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCitationExample Context triple: [M.G.L., typicalCitationExample, "G.L. c. 93A" or "M.G.L. c. 93A"]
-
A.
typicalCitation
Indicates that one entity is commonly or characteristically cited as a reference or source for another entity.
-
B.
citationFormExample
chosen
Indicates that an example is provided illustrating the standard or canonical citation form of an expression or lexical item.
-
C.
citationIn
Indicates that one work cites, references, or otherwise acknowledges another work as a source.
-
D.
citationType
Indicates the specific kind or category of citation relationship that one entity has to another (e.g., reference, quotation, acknowledgment).
-
E.
citationAs
Indicates that one entity is cited or referenced in the role or capacity specified by another entity (such as a particular work, version, or context).
- 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_69eeb31c925881909b597f6e40056d28 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69ff0b6bc4a88190bf1d38c6ea26bcdc |
completed | May 9, 2026, 10:24 a.m. |
| PD | Predicate disambiguation | batch_69ff082a22f4819095ded971dbd8ea7b |
completed | May 9, 2026, 10:10 a.m. |
Created at: April 27, 2026, 4:08 a.m.