Triple
T15636623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs. Mott |
E375960
|
entity |
| Predicate | causeOfHusbandDeath |
P119548
|
FINISHED |
| Object | suicide |
—
|
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: suicide | Statement: [Mrs. Mott, causeOfHusbandDeath, suicide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causeOfHusbandDeath Context triple: [Mrs. Mott, causeOfHusbandDeath, suicide]
-
A.
newsOfHusbandsDeathBroughtBy
Indicates that the news of a husband's death is delivered or communicated by a particular person or source.
-
B.
firstHusbandDeath
Indicates that the woman's first husband has died, marking the end of that marital relationship by his death.
-
C.
spouseDeath
Indicates that one person's spouse has died, marking the event of the spouse's death in relation to that person.
-
D.
spousePlaceOfDeath
Indicates the location where a person's spouse died.
-
E.
firstLearnsOfHusbandsDeathFrom
Indicates that a person’s first awareness or discovery of her husband’s death comes from a specified source or informant.
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eba51f08190ac5d9de7fc89405a |
completed | April 16, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69deda868d4481908f4bce1c64d2902a |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f3016c8190ac68d76e65e07af4 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:14 a.m.