Triple
T20184883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lawndale High School |
E492827
|
entity |
| Predicate | hasStaffMember |
P36133
|
FINISHED |
| Object |
Ms. Manson
Ms. Manson is a teacher at Lawndale High School in the animated television series "Daria."
|
E1415881
|
NE FINISHED |
How this triple was built (4 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: Ms. Manson | Statement: [Lawndale High School, hasStaffMember, Ms. Manson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ms. Manson Context triple: [Lawndale High School, hasStaffMember, Ms. Manson]
-
A.
Ms. Thing
Ms. Thing is a Jamaican dancehall singer best known for her early-2000s collaborations and hits within the reggae and dancehall scene.
-
B.
Maura
Maura is a feminine given name commonly used in English-speaking countries, often considered a variant of Mary or Maureen.
-
C.
Maura
Maura is a village in Nannestad Municipality in Viken county, Norway, known as a residential community with local services and proximity to Oslo Airport Gardermoen.
-
D.
Ms. Kane
Ms. Kane is a performer best known for her work in the production "Adrenaline Rush," where she delivers high-energy, dynamic performances.
-
E.
Mrs. X
Mrs. X is the wealthy, demanding Manhattan socialite and employer of the protagonist nanny in the novel and film "The Nanny Diaries."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ms. Manson Triple: [Lawndale High School, hasStaffMember, Ms. Manson]
Generated description
Ms. Manson is a teacher at Lawndale High School in the animated television series "Daria."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ms. Manson Target entity description: Ms. Manson is a teacher at Lawndale High School in the animated television series "Daria."
-
A.
Ms. Thing
Ms. Thing is a Jamaican dancehall singer best known for her early-2000s collaborations and hits within the reggae and dancehall scene.
-
B.
Maura
Maura is a feminine given name commonly used in English-speaking countries, often considered a variant of Mary or Maureen.
-
C.
Maura
Maura is a village in Nannestad Municipality in Viken county, Norway, known as a residential community with local services and proximity to Oslo Airport Gardermoen.
-
D.
Ms. Kane
Ms. Kane is a performer best known for her work in the production "Adrenaline Rush," where she delivers high-energy, dynamic performances.
-
E.
Mrs. X
Mrs. X is the wealthy, demanding Manhattan socialite and employer of the protagonist nanny in the novel and film "The Nanny Diaries."
- 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e668f199688190a42094cce220f6f2 |
completed | April 20, 2026, 5:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a083c81d6f48190b851d90089367f0f |
completed | May 16, 2026, 9:44 a.m. |
| NEDg | Description generation | batch_6a083d3196148190847a625ad09762a2 |
completed | May 16, 2026, 9:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a083e04aab88190a1e0219427d8d0e1 |
completed | May 16, 2026, 9:51 a.m. |
Created at: April 11, 2026, 11:36 p.m.