Triple
T15071860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Poet |
E379895
|
entity |
| Predicate | hasTitleCharacterAlias |
P117206
|
FINISHED |
| Object | the Poet |
—
|
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: the Poet | Statement: [The Poet, hasTitleCharacterAlias, the Poet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleCharacterAlias Context triple: [The Poet, hasTitleCharacterAlias, the Poet]
-
A.
hasTitleCharacterRelation
Indicates a relationship where a title (such as a work or publication) is associated with or linked to a specific character appearing in it.
-
B.
isTitleCharacterString
Indicates that a given string represents the title text associated with an entity.
-
C.
hasTitleLetter
Indicates that an entity possesses a specific letter or character within its title.
-
D.
hasTitleCharacterLocation
Indicates that a title or heading is associated with a specific character’s location within a text or media.
-
E.
hasTitleCharacterTrait
Indicates that a title is associated with a specific character trait of an entity.
- 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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dff7f86df48190b3a2cf441fefb477 |
completed | April 15, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69deb95a182081908fffc4402b02a394 |
completed | April 14, 2026, 10:02 p.m. |
| PDg | Predicate description generation | batch_69dec71e8dcc81908badc834b6ccf273 |
completed | April 14, 2026, 11 p.m. |
Created at: April 10, 2026, 3:02 a.m.