Triple
T13124236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MXVER |
E311802
|
entity |
| Predicate | lastThreeCharacters |
P108177
|
FINISHED |
| Object | VER |
—
|
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: VER | Statement: [MXVER, lastThreeCharacters, VER]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lastThreeCharacters Context triple: [MXVER, lastThreeCharacters, VER]
-
A.
lastLetter
Indicates that one entity is the final character in the written or spelled form of another entity.
-
B.
lastStanzaLetter
Indicates that a given letter is the final letter of the last stanza in a text or poem.
-
C.
hasLastThreeLettersMeaning
Indicates that the last three letters of one entity (typically a word or string) together form a meaningful unit or have a specific semantic significance.
-
D.
lastWordsTo
Indicates that one entity spoke their final words or message directed specifically to another entity.
-
E.
lastWords
Indicates the final words spoken or written by an entity (typically a person) before their death or the end of a significant event.
- 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_69d806a9fe888190b081e2d9ea665d6c |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9819946808190b41335fb1054accd |
completed | April 10, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69d98043a74c81908648e6cd0b4c7f71 |
completed | April 10, 2026, 10:57 p.m. |
| PDg | Predicate description generation | batch_69d98134df64819084a5674f9475dcc2 |
completed | April 10, 2026, 11:01 p.m. |
Created at: April 9, 2026, 9:07 p.m.