Triple
T10842746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lizzie Fletcher |
E255929
|
entity |
| Predicate | represents |
P129
|
FINISHED |
| Object | TX-07 |
E255929
|
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: TX-07 | Statement: [Lizzie Fletcher, represents, TX-07]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TX-07 Context triple: [Lizzie Fletcher, represents, TX-07]
-
A.
TX-07
chosen
TX-07 is a United States congressional district located in the Houston area of Texas, represented in the U.S. House of Representatives.
-
B.
TX-06
TX-06 is the abbreviated designation for Texas's 6th congressional district, a U.S. House of Representatives district covering parts of the Dallas–Fort Worth region.
-
C.
TX-05
TX-05 is the standard abbreviated designation for Texas's 5th congressional district in the United States House of Representatives.
-
D.
TX-10
TX-10 is the commonly used abbreviation for Texas's 10th congressional district, a U.S. House of Representatives district covering parts of central Texas.
-
E.
TX-27
TX-27 is a U.S. congressional district in Texas that elects a representative to the United States House of Representatives.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d750ce40108190895c477553195fe4 |
completed | April 9, 2026, 7:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69deb153de988190bd48f1c1980d7ca2 |
completed | April 14, 2026, 9:27 p.m. |
Created at: April 8, 2026, 9:19 p.m.