Triple
T5297059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donner Party |
E119880
|
entity |
| Predicate | memberCountAtDeparture |
P9077
|
FINISHED |
| Object | around 87 |
—
|
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: around 87 | Statement: [Donner Party, memberCountAtDeparture, around 87]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: memberCountAtDeparture Context triple: [Donner Party, memberCountAtDeparture, around 87]
-
A.
previousNumberOfMembers
Indicates the number of members an entity had at an earlier or prior point in time.
-
B.
hadNumberOfMembers
Indicates that an entity possessed or was associated with a specific count of members at a given time or in a given context.
-
C.
originalNumberOfMembers
chosen
Indicates the initial total count of members in a group or organization before any changes such as additions or removals.
-
D.
memberCountAtPeak
Indicates the highest number of members that an entity (such as a group or organization) has had at any point in time.
-
E.
numberOfFullMembers
Indicates the total count of entities that hold full membership status within a specified group or organization.
- 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_69bd446f22b88190b6a47fb91c68a3e7 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd8e44e7c881909b241b2fec366038 |
completed | March 20, 2026, 6:13 p.m. |
| PD | Predicate disambiguation | batch_69bd845097ac81909678624c4907fda4 |
completed | March 20, 2026, 5:30 p.m. |
Created at: March 20, 2026, 1:53 p.m.