Triple
T38048765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Alexandre Manette |
E949694
|
entity |
| Predicate | learnedShoemaking |
P189909
|
FINISHED |
| Object | during imprisonment in the Bastille |
—
|
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: during imprisonment in the Bastille | Statement: [Dr. Alexandre Manette, learnedShoemaking, during imprisonment in the Bastille]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: learnedShoemaking Context triple: [Dr. Alexandre Manette, learnedShoemaking, during imprisonment in the Bastille]
-
A.
traditionalFootwear
Indicates that the relationship involves footwear that is characteristic of, or historically associated with, a particular culture, region, or tradition.
-
B.
shoeLine
Indicates a relationship where a shoe is part of, or belongs to, a particular product line or collection of shoes.
-
C.
shoeCount
Indicates the number of shoes associated with a given entity.
-
D.
shoeIsFoundBy
Indicates that a shoe is discovered, obtained, or located by a particular agent or entity.
-
E.
depictsFootwear
Indicates that one entity visually represents or shows footwear associated with another 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_69f76f000cf081908c11fb5443b392e6 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fc44c7e73c819082d4fc1900fb9632 |
completed | May 7, 2026, 7:52 a.m. |
| PD | Predicate disambiguation | batch_69fbc8efffbc8190a139798ad1880526 |
completed | May 6, 2026, 11:04 p.m. |
| PDg | Predicate description generation | batch_69fc44c67118819088accfeded7b449e |
completed | May 7, 2026, 7:52 a.m. |
Created at: May 3, 2026, 4:20 p.m.