Triple
T24059367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen Anne, Maryland |
E595898
|
entity |
| Predicate | familiesCensus2000 |
P31487
|
FINISHED |
| Object | 45 |
—
|
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: 45 | Statement: [Queen Anne, Maryland, familiesCensus2000, 45]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: familiesCensus2000 Context triple: [Queen Anne, Maryland, familiesCensus2000, 45]
-
A.
numberOfFamilies
chosen
Indicates the total count of distinct family units associated with a given entity or context.
-
B.
householdsCensus2010
Indicates the number of households recorded in the 2010 census for a given geographic or administrative unit.
-
C.
medianFamilyIncome2000USD
Indicates the median income earned by families in the year 2000, expressed in U.S. dollars.
-
D.
demographicsOtherRacesPresent2000
Indicates that, in the year 2000, the demographic data show the presence of racial groups categorized as "other races" beyond the primary race categories.
-
E.
macroFamilyStatus
Indicates the broad genealogical relationship between languages or language families at the macro-family level.
- 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_69e288c184b081909f1f1751fb8e299a |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1da543e74819083ebea41ca20e0e9 |
completed | April 29, 2026, 10:15 a.m. |
| PD | Predicate disambiguation | batch_69f1764b1d4c8190b12590c6339c31c1 |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 10:36 p.m.