Triple
T3051919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | family of Mark Twain |
E83588
|
entity |
| Predicate | hasTragicEvent |
P22468
|
FINISHED |
| Object | Death of Langdon Clemens (1872) |
—
|
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: Death of Langdon Clemens (1872) | Statement: [family of Mark Twain, hasTragicEvent, Death of Langdon Clemens (1872)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTragicEvent Context triple: [family of Mark Twain, hasTragicEvent, Death of Langdon Clemens (1872)]
-
A.
hasTragicPast
Indicates that an entity has experienced a significantly sorrowful or traumatic history that influences its present state or characterization.
-
B.
hadEvent
chosen
Indicates that an entity experienced, hosted, or was associated with a specific event at some point in time.
-
C.
hasTragicEnding
Indicates that the event, story, or situation concludes with a sorrowful, disastrous, or otherwise deeply unfortunate outcome.
-
D.
hasDisaster
Indicates that an entity experiences, is affected by, or is associated with a disaster event.
-
E.
hasNotableIncident
Indicates that an entity is associated with a significant or noteworthy event, occurrence, or incident.
- 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_69ad8b24924c8190a9bb6f61d519e4ae |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9bf274f88190a759f9ce3da47c35 |
completed | March 8, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69ad962195388190856013a2519c2b0f |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:01 p.m.