Triple
T35966499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Daniel J. Morrell shipwreck |
E1040155
|
entity |
| Predicate | victimCountApprox |
P150701
|
FINISHED |
| Object | about 28 crew members lost |
—
|
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: about 28 crew members lost | Statement: [SS Daniel J. Morrell shipwreck, victimCountApprox, about 28 crew members lost]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: victimCountApprox Context triple: [SS Daniel J. Morrell shipwreck, victimCountApprox, about 28 crew members lost]
-
A.
numberOfVictimsKilled
Indicates the count of victims who were killed as a result of the referenced event or action.
-
B.
numberOfVictimsClaimed
Indicates the reported count of victims associated with a particular event, incident, or action.
-
C.
numberOfVictimsConfirmed
Indicates the confirmed count of victims associated with an event, incident, or situation.
-
D.
killedManyVictims
Indicates that an entity has killed a large number of distinct victims.
-
E.
hasApproximateNumberOfVictims
chosen
Indicates that an entity is associated with an estimated, non-exact count of victims.
- 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_69f76e26b21081909fd9ffb3aff6c77a |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7acaec1508190a38f2ac9cc5383e7 |
completed | May 3, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f7ab75387c819091afc3c2128eb903 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:07 p.m.