Triple
T34780749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hester |
E1002651
|
entity |
| Predicate | perceivesHouseAs |
P181608
|
FINISHED |
| Object | always needing more money |
—
|
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: always needing more money | Statement: [Hester, perceivesHouseAs, always needing more money]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: perceivesHouseAs Context triple: [Hester, perceivesHouseAs, always needing more money]
-
A.
typeOfHouse
Indicates the specific category or kind of house associated with an entity (e.g., apartment, detached house, townhouse).
-
B.
residenceType
Indicates the kind or category of dwelling or living arrangement associated with an entity.
-
C.
housingPattern
Indicates the typical arrangement or distribution of housing units or residential structures within a given area or context.
-
D.
keeperHouseStyle
Indicates the architectural or design style associated with a keeper’s house (e.g., lighthouse keeper’s residence).
-
E.
houseUse
Indicates how a house or dwelling is used or purposed (e.g., residential, commercial, mixed-use).
- F. None of above. chosen
Provenance (4 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_69f76db30a108190bb57ca95b873e5bb |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f77ffa6b68819090257fed3802c239 |
completed | May 3, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69f7795978c481909e152cd1bd02dd07 |
completed | May 3, 2026, 4:35 p.m. |
| PDg | Predicate description generation | batch_69f77ff804f08190b431a31e6179ace4 |
completed | May 3, 2026, 5:03 p.m. |
Created at: May 3, 2026, 3:59 p.m.