Triple
T684220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Langdon family |
E13248
|
entity |
| Predicate | hasNotableDescendant |
P17517
|
FINISHED |
| Object | Mark Twain’s children |
—
|
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: Mark Twain’s children | Statement: [Langdon family, hasNotableDescendant, Mark Twain’s children]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableDescendant Context triple: [Langdon family, hasNotableDescendant, Mark Twain’s children]
-
A.
hasAncestor
Indicates that one entity is an ancestor (direct or indirect, such as a parent, grandparent, etc.) of another entity in a genealogical or hierarchical lineage.
-
B.
hasNoChildren
Indicates that the subject entity does not have any children associated with it.
-
C.
hasNotableSegment
Indicates that an entity includes or contains a specific segment, part, or portion that is considered notable or significant in some way.
-
D.
hasNotableIntersection
Indicates that two entities intersect or cross at a point that is considered significant or noteworthy in some context.
-
E.
hasNotableFeature
Indicates that an entity possesses a specific characteristic, trait, or attribute that is considered significant or noteworthy.
- 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_69a4933e0f98819097d22766c49b61b8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a0725c708190aa6edfee742ca4e6 |
completed | March 1, 2026, 8:24 p.m. |
| PD | Predicate disambiguation | batch_69a49d1f0ccc819088c1527beabcb718 |
completed | March 1, 2026, 8:10 p.m. |
| PDg | Predicate description generation | batch_69a49df19c9481909cc9bc33ed7f011b |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:36 p.m.