Triple
T2305112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tricia McMillan |
E51818
|
entity |
| Predicate | meetsArthurDentAt |
P1220
|
FINISHED |
| Object | party in Islington |
—
|
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: party in Islington | Statement: [Tricia McMillan, meetsArthurDentAt, party in Islington]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meetsArthurDentAt Context triple: [Tricia McMillan, meetsArthurDentAt, party in Islington]
-
A.
meetsAs
Indicates that two entities encounter or come together at the same place and time, typically in a planned or recognized interaction.
-
B.
meets
chosen
Indicates that two or more entities come together at the same place and time, typically for interaction or a shared purpose.
-
C.
meetsBetween
Indicates that one entity meets or encounters another at some point between two specified reference points or times.
-
D.
meetsUnder
Indicates that one entity encounters or comes together with another entity in a context where it is subordinate to, governed by, or occurring within the scope or authority of a third entity or condition.
-
E.
meetsVia
Indicates that two entities come into contact or interact with each other through a specified intermediary medium, channel, or mechanism.
- 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_69a88b0bb30c81908ded03b006d29387 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abce1f4f0c8190a714e4dcb8449f7e |
completed | March 7, 2026, 7:05 a.m. |
| PD | Predicate disambiguation | batch_69abc58ce2a081908ce2f0cadd92e9f8 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.