Triple
T38667499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2009 Seattle mayoral election |
E940491
|
entity |
| Predicate | primarySecondFinisher |
P206609
|
FINISHED |
| Object | Mike McGinn |
E277549
|
NE 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: Mike McGinn | Statement: [2009 Seattle mayoral election, primarySecondFinisher, Mike McGinn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primarySecondFinisher Context triple: [2009 Seattle mayoral election, primarySecondFinisher, Mike McGinn]
-
A.
secondaryTo
Indicates that one condition, event, or factor occurs as a consequence of, or is caused by, another primary condition, event, or factor.
-
B.
secondaryProducts
Indicates that certain entities arise as secondary or byproduct outputs from a primary process, activity, or production.
-
C.
secondaryBrand
Indicates that one brand is a subordinate, supporting, or less prominent brand in relation to a primary brand.
-
D.
secondaryCup
Indicates that one cup serves as a secondary or backup cup in relation to a primary cup.
-
E.
secondarySingle
Indicates that an entity serves as a secondary, but singular, counterpart or role in relation to another primary entity.
- F. None of above. chosen
Provenance (5 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_69f76edfde348190bf6529d9f49ecd62 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a42158606688190bb156d99bb0b556c |
completed | June 29, 2026, 6:49 a.m. |
| PD | Predicate disambiguation | batch_6a037a2026248190b894436a578d79ac |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037c85e308819083dd67b96f457659 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:33 p.m.