Triple
T768669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bliss copy |
E16230
|
entity |
| Predicate | hasTextOrder |
P19744
|
FINISHED |
| Object | final revised text of the Gettysburg Address |
—
|
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: final revised text of the Gettysburg Address | Statement: [Bliss copy, hasTextOrder, final revised text of the Gettysburg Address]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTextOrder Context triple: [Bliss copy, hasTextOrder, final revised text of the Gettysburg Address]
-
A.
hasOrder
Indicates that one entity possesses, is associated with, or is characterized by a specific order, sequence, or arrangement relative to others.
-
B.
hasText
Indicates that an entity is associated with or contains a specific piece of textual content.
-
C.
hasBasicWordOrder
Indicates the typical sequence in which core sentence elements (such as subject, verb, and object) are ordered in a language.
-
D.
hasTextOpening
Indicates that an entity begins with or contains a specified initial segment of text.
-
E.
hasRankOrder
Indicates that one entity is ordered or positioned relative to others according to a specific ranking or sequence.
- 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_69a49369a0848190af883934cee3db4c |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a765ba688190ab328bb159583077 |
completed | March 1, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69a4a5074c788190a74fc20ad24e2d26 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a7648a6c8190a9051a3d177ff7e2 |
completed | March 1, 2026, 8:53 p.m. |
Created at: March 1, 2026, 7:37 p.m.