Triple
T27195623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexander Low |
E683588
|
entity |
| Predicate | associatedWithNotableFieldOfNameBearer |
P106126
|
FINISHED |
| Object | bridge design |
—
|
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: bridge design | Statement: [Alexander Low, associatedWithNotableFieldOfNameBearer, bridge design]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithNotableFieldOfNameBearer Context triple: [Alexander Low, associatedWithNotableFieldOfNameBearer, bridge design]
-
A.
fieldOfNotableBearer
chosen
Indicates the professional or activity domain in which a notable bearer of a name, title, or identifier is recognized.
-
B.
associatedWithNotableBearerNationality
Indicates that an entity is connected to the nationality of a notable bearer of a related name or title.
-
C.
notableField
Indicates the field, discipline, or area of activity for which an entity is especially known or distinguished.
-
D.
associatedWithNotableAchievementOfNameBearer
Indicates a relationship where an entity is linked to a notable achievement accomplished by a person who bears a particular name.
-
E.
notableFieldOfRecipients
Indicates that the recipients are notable or recognized specifically in a particular field or area of expertise.
- 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_69eefad1fd5c8190a4a46ea6afe58bfa |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69ffc516d1908190b475f5a6156b0ca8 |
completed | May 9, 2026, 11:36 p.m. |
| PD | Predicate disambiguation | batch_69ffc4a946e08190b3535a5dc15ac484 |
completed | May 9, 2026, 11:35 p.m. |
Created at: April 27, 2026, 9:34 a.m.