Triple
T4517700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Siege at Peking |
E103191
|
entity |
| Predicate | hasNotablePersonDescribed |
P20309
|
FINISHED |
| Object | Herbert G. Squiers |
—
|
NE NERFINISHED |
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: Herbert G. Squiers | Statement: [The Siege at Peking, hasNotablePersonDescribed, Herbert G. Squiers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotablePersonDescribed Context triple: [The Siege at Peking, hasNotablePersonDescribed, Herbert G. Squiers]
-
A.
hasNotablePersonAsFace
Indicates that an entity is publicly represented or symbolized by a specific notable person, such as a spokesperson, ambassador, or brand face.
-
B.
hasNotablePersonRaisedHere
Indicates that a notable person spent their formative or upbringing years in the referenced place.
-
C.
notablePersonDiscussed
chosen
Indicates that the subject entity includes or features a discussion about the referenced notable person.
-
D.
depictsNotablePerson
Indicates that one entity visually represents or portrays a person who is considered notable or significant.
-
E.
notableFor
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
- 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_69bd43dba59881908cf59b31df8c7ae1 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd572933408190b67c4ef6a7babe75 |
completed | March 20, 2026, 2:18 p.m. |
| PD | Predicate disambiguation | batch_69bd521abea48190b3e758a1f98dd55e |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:02 p.m.