Triple
T17714658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph Merrick |
E442163
|
entity |
| Predicate | hadQuality |
P6861
|
FINISHED |
| Object | politeness |
—
|
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: politeness | Statement: [Joseph Merrick, hadQuality, politeness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadQuality Context triple: [Joseph Merrick, hadQuality, politeness]
-
A.
quality
chosen
Indicates that an entity possesses a particular attribute, characteristic, or degree of excellence that defines how good, suitable, or effective it is in a given context.
-
B.
hadCustom
Indicates that an entity previously possessed or was associated with a customized or user-defined version of something.
-
C.
supportsQuality
Indicates that one entity contributes to maintaining, enhancing, or ensuring the quality or standard of another entity or process.
-
D.
hadIssue
Indicates that an entity experienced, encountered, or was affected by a particular problem, defect, or difficulty.
-
E.
hadOrgan
Indicates that an entity previously possessed or contained a specific organ as part of its body.
- 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_69d8b9ec79688190b86bdcef85a7b3aa |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4747f217081909010f396caaf03be |
completed | April 19, 2026, 6:21 a.m. |
| PD | Predicate disambiguation | batch_69e3cde601d4819097903f471f1fe99a |
completed | April 18, 2026, 6:31 p.m. |
Created at: April 10, 2026, 10:06 a.m.